Journal articles: 'Artificial intelligence service agents'

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Sonntag, Michael. "AGENTS AS WEB SERVICE PROVIDERS: SINGLE AGENTS OR MAS?" Applied Artificial Intelligence 20, no. 2-4 (February 2006): 203–27. http://dx.doi.org/10.1080/08839510500484223.

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BLAKE, M. BRIAN, SIMON PARSONS, and TERRY R. PAYNE. "The synergy of electronic commerce, agents, and semantic Web services." Knowledge Engineering Review 19, no. 2 (June 2004): 175–80. http://dx.doi.org/10.1017/s0269888904000153.

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Advancements in software agents and Semantic Web service technologies are generally enhancing the landscape of electronic commerce. Semantic Web service technologies promise the standardisation and discoverability of software capabilities for network-enabled organisations. Moreover, with the addition of the intelligence and autonomy of software agents, transactions may be equally automated for consumer-to-consumer, business-to-consumer, and business-to-business collaborations. The 2003 Workshop on Electronic Commerce, Agents, and Semantic Web Services was held in conjunction with the International Conference on Electronic Commerce (ICEC2003). The purpose of this workshop was to bring together researchers and practitioners in the areas of electronic commerce, agents, and Semantic Web services to discuss the state-of-art in each individual area in addition to the synergies among the areas. This paper contains a summary of the workshop presentations and a discussion of next steps for Semantic Web services created in the working sessions concluding the workshop.

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PELACHAUD, CATHERINE, and ISABELLA POGGI. "Multimodal embodied agents." Knowledge Engineering Review 17, no. 2 (June 2002): 181–96. http://dx.doi.org/10.1017/s0269888902000218.

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1 Believable interactive embodied agentsAmong the goals of research on autonomous agents one important aim is to build believable interactive embodied agents that are apt to application to friendly interfaces in e-commerce, tourist and service query systems, entertainment (e.g. synthetic actors) and education (pedagogical agents, agents for help and instruction to the hearing impaired).

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HONARI, SINA, BRIGITTE JAUMARD, and JAMAL BENTAHAR. "UNCERTAINTY-BASED TRUST ESTIMATION IN A MULTI-VALUED TRUST ENVIRONMENT." International Journal on Artificial Intelligence Tools 22, no. 05 (October 2013): 1360003. http://dx.doi.org/10.1142/s0218213013600038.

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Despite the widespread usage of the evaluation mediums for online services by the clients, there is a requirement for a trust evaluation tool that provides the clients with the degree of trustworthiness of the service providers. Such a tool can provide increased familiarity with unknown third party entities, e.g. service providers, especially when those entities neither project completely trustworthy nor totally untrustworthy behaviour. Indeed, developing some metrics for trust evaluation under uncertainty can come handy, e.g., for customers interested in evaluating the trustworthiness of an unknown service provider throughout queries to other customers of unknown reliability. In this research, we propose an evaluation metric to estimate the degree of trustworthiness of an unknown agent, say aD, through the information acquired through a group of agents who have interacted with agent aD. This group of agents is assumed to have an unknown degree of reliability. In order to tackle the uncertainty associated with the trust of these set of unknown agents, we suggest to use possibility distributions. Later, we introduce a new certainty metric to measure the degree of agreement in the information reported by the group of agents in A on agent aD. Fusion rules are then used to measure an estimation of the agent aD’s degree of trustworthiness. To the best of our knowledge, this is the first work that estimates trust, out of empirical data, subject to some uncertainty, in a discrete multi-valued trust domain. Finally, numerical experiments are presented to validate the proposed tools and metrics.

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Choi, Key-sun. "Artificial Intelligence and Artificial Language: Agents in Information Architecture for Intelligent Distributed Multilingual Document Retrieval Service." Journal of Universal Language 2, no. 1 (March 31, 2001): 34–50. http://dx.doi.org/10.22425/jul.2001.2.1.34.

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Jonker, Catholijn M., Koen V. Hindriks, Pascal Wiggers, and Joost Broekens. "Negotiating Agents." AI Magazine 33, no. 3 (September 20, 2012): 79. http://dx.doi.org/10.1609/aimag.v33i3.2421.

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Negotiation is a complex emotional decision-making process aiming to reach an agreement to exchange goods or services. From an agent technological perspective creating negotiating agents that can support humans with their negotiations is an interesting challenge. Already more than a decade, negotiating agents can outperform human beings (in terms of deal optimality) if the negotiation space is well-understood. However, the inherent semantic problem and the emotional issues involved make that negotiation cannot be handled by artificial intelligence alone, and a human-machine collaborative system is required. This article presents research goals, challenges, and an approach to create the next generation of negotiation support agents.

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Goltz, Nachshon (Sean), John Zeleznikow, and Tracey Dowdeswell. "From the Tree of Knowledge and the Golem of Prague to Kosher Autonomous Cars: The Ethics of Artificial Intelligence Through Jewish Eyes." Oxford Journal of Law and Religion 9, no. 1 (February 1, 2020): 132–56. http://dx.doi.org/10.1093/ojlr/rwaa015.

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Abstract This article discusses the regulation of artificial intelligence from a Jewish perspective, with an emphasis on the regulation of machine learning and its application to autonomous vehicles and machine learning. Through the Biblical story of Adam and Eve as well as Golem legends from Jewish folklore, we derive several basic principles that underlie a Jewish perspective on the moral and legal personhood of robots and other artificially intelligent agents. We argue that religious ethics in general, and Jewish ethics in particular, show us that the dangers of granting moral personhood to robots and in particular to autonomous vehicles lie not in the fact that they lack a soul—or consciousness or feelings or interests—but because to do so weakens our own ability to develop as fully autonomous legal and moral persons. Instead, we argue that existing legal persons should continue to maintain legal control over artificial agents, while natural persons assume ultimate moral responsibility for choices made by artificial agents they employ in their service. In the final section of the article we discuss the trolley dilemma in the context of governing autonomous vehicles and sketch out an application of Jewish ethics in a case where we are asking Artificial Intelligence to make life and death decisions. Our novel contribution is two-fold; first, we bring a religious approach to the discussion of the ethics of Artificial Intelligence which has hitherto been dominated by secular Western philosophies; second, we raise the idea that artificial entities who are trained through machine learning can be ethically trained in much the same way that human are—through reading and reflecting on core religious texts. This is both a way of ensuring the ethical regulation of artificial intelligence, but also promotes other core values of regulation, such as democratic engagement and user choice.

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Gunasekera, Kutila, Seng Wai Loke, Arkady Zaslavsky, and Shonali Krishnaswamy. "IMPROVING EFFICIENCY OF SERVICE-ORIENTED CONTEXT-DRIVEN SOFTWARE AGENTS." Cybernetics and Systems 42, no. 5 (June 2011): 324–40. http://dx.doi.org/10.1080/01969722.2011.595336.

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SMIRNOV, ALEXANDER, TATIANA LEVASHOVA, NIKOLAY SHILOV, and ALEXEY KASHEVNIK. "HYBRID TECHNOLOGY FOR SELF-ORGANIZATION OF RESOURCES OF PERVASIVE ENVIRONMENT FOR OPERATIONAL DECISION SUPPORT." International Journal on Artificial Intelligence Tools 19, no. 02 (April 2010): 211–29. http://dx.doi.org/10.1142/s0218213010000121.

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The paper addresses the development of a hybrid technology for operational decision support in a pervasive environment. The technology encompasses the idea of implementing a decision support system as a set of Web-services. The Web-services are intended to form an ad-hoc collaborative environment, whose members cooperate with an objective of serving the current needs according to the decision situation. The collaborative environment is made up of resources of a pervasive environment. The technology is focused on three types of resources to be organized: information, problem-solving, and acting, and is supported by a service-based architecture of the decision support system providing types of Web-services needed for this technology implementation. The hybrid technology integrates technologies of ontology management, context management, constraint satisfaction, Web-services, profiling, and intelligent agents. The technology application is illustrated by the decision support for dynamic logistics.

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Al-Araj, Reem, Hossam Haddad, Maha Shehadeh, Elina Hasan, and Mohammad Yousef Nawaiseh. "The Effect of Artificial Intelligence on Service Quality and Customer Satisfaction in Jordanian Banking Sector." WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS 19 (December 13, 2022): 1929–47. http://dx.doi.org/10.37394/23207.2022.19.173.

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The study emphasizes the importance of Artificial Intelligence (AI) and its applications on the service quality provided by Jordanian banks for their customer satisfaction. This research paper thoroughly reviews the literature on the numerous emergent applications of artificial intelligence and its impact on the banking sector. A rigorous study of the available literature is conducted to examine AI's uses in banking. Artificial intelligence improves the banking experience for millions of clients and employees by providing credit score checking, system failure prediction, emergency alarm systems, fraud detection, phishing website detection, liquidity risk assessment, customer loyalty evaluation and intelligence systems by reducing the employee workload. A questionnaire gathered data from 270 consumers in Jordan's banking sector. The SPSS program used exploratory factor analysis to statistically evaluate the sample data to determine service quality and customer satisfaction. The results show that the updated SERVQUAL Model extracted five subscales instead of the eight in the original model. The extracted subscales were tangibility, assurance, reliability, responsiveness, and empathy. According to this study, artificial intelligence is statistically relevant to service quality and customer satisfaction. The updated SERVQUAL model, according to the authors, helps address customer satisfaction in the banking sector. The research findings suggest that the demand for artificial intelligence in the Jordanian banking sector is equally essential for the customers; thus, there should be an optimal balance between virtual and human agents based on the customers' requirements and preferences. Further, this study found practical implications of using AI in banking, particularly those related to Jordanian customer perception.

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Wei, Fang, Dai Sheng, and Wang Lili. "Evolutionary Model and Simulation Research of Collaborative Innovation Network: A Case Study of Artificial Intelligence Industry." Discrete Dynamics in Nature and Society 2018 (November 11, 2018): 1–13. http://dx.doi.org/10.1155/2018/4371528.

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Based on integrating the fundamental attribute and the unique property of the collaborative innovation network, this paper establishes a collaborative innovation network model of Artificial Intelligence industry through depicting external stimulus conversion progresses and behaviors of network heterogeneous agents. Heterogeneous agents are the network elements of the model which regards the stimulus response as the evolutionary mechanism. Tencent is one of the largest Internet integrated service providers and one of the Internet companies with the largest number of service users in China, which has also set its sights on the development of the AI industry. Taking Tencent’s patent cooperation network in the field of Artificial Intelligence as an example and using system simulation method, we analyze the evolutionary law of the collaborative innovation network topology structure, the coupling evolution phenomenon of the knowledge and the network topology structure, distinct roles that agents play in the network, and relationship between the agents’ openness and the knowledge flow efficiency. We find the phenomenon of small world emergence more than once through the evolution of collaborative innovation network, whose degrees and reasons are also distinctive. There exists coupling evolution between the technological knowledge and the network structure. The collaborative innovation network is always oriented towards competitive industries. The agents’ openness has an essential influence on the lifting range of the technological knowledge. Strengthening the main position of enterprises in AI technological innovation and enhancing the degree of openness among heterogeneous agents are a powerful guarantee for improving the performance of collaborative innovation.

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Antunes, Mark, Vincent Armant, Kenneth N. Brown, Daniel Desmond, Guillaume Escamocher, Anne-Marie George, Diarmuid Grimes, et al. "Assigning and Scheduling Service Visits in a Mixed Urban/Rural Setting." International Journal on Artificial Intelligence Tools 29, no. 03n04 (June 2020): 2060007. http://dx.doi.org/10.1142/s0218213020600076.

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This papera describes a maintenance scheduling application, which was developed together with an industrial partner. This is a highly combinatorial decision process, to plan and schedule the work of a group of travelling repair technicians, which perform preventive and corrective maintenance tasks at customer locations. Customers are located both in urban areas, where many customers are in close proximity, and in sparsely populated rural areas, where the travel time between customer sites is significant. To balance the workload for the agents, we must consider both the productive working time, as well as the travel between locations. As the monolithic problem formulation is unmanageable, we introduce a problem decomposition into multiple sequential steps, that is compatible with current management practice. We present and compare different models for the solution steps, and discuss results on datasets provided by the industrial partner.

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Lalicic, Lidija, and Christian Weismayer. "Consumers’ reasons and perceived value co-creation of using artificial intelligence-enabled travel service agents." Journal of Business Research 129 (May 2021): 891–901. http://dx.doi.org/10.1016/j.jbusres.2020.11.005.

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Zheng, Yongqing, Han Yu, Lizhen Cui, Chunyan Miao, Cyril Leung, Yang Liu, and Qiang Yang. "Addressing the Challenges of Government Service Provision with AI." AI Magazine 41, no. 1 (April 13, 2020): 33–43. http://dx.doi.org/10.1609/aimag.v41i1.5195.

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In complete contract theory, the main approach to limit moral hazard is through modifying incentives for the agents. However, such modifications are not always feasible. One prominent example is Chinese government service provision. Over the years, it has been plagued with inefficiencies as a result of moral hazard. Previous attempts to address these challenges are not effective, as reforms on civil servant incentives face stiff hindrance. In this article, we report an alternative platform — SmartHS — to address these challenges in China without modifying incentives. Through dynamic teamwork, automation of key steps involved in service provision, and improved transparency with the help of artificial intelligence, it places civil servants into an environment that promotes efficiency and reduces the opportunities for moral hazard. Deployment tests in the field of social insurance service provision in three Chinese cities involving close to 3 million social insurance service cases per year demonstrated that the proposed approach significantly reduces moral hazard symptoms. The findings are useful for informing current policy discussions on government reform in China and have the potential to address long-standing problems in government service provision to benefit almost one-fifth of the world’s population.

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Wang, Hongbing, Jie Zhang, Cheng Wan, Shizhi Shao, and Robin Cohen. "Qualitative preference-based service selection for multiple agents." Web Intelligence and Agent Systems: An International Journal 11, no. 3 (2013): 263–82. http://dx.doi.org/10.3233/wia-130274.

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GAO, S., H. WANG, Y. WANG, W. SHEN, and S. YEUNG. "Web-service-agents-based family wealth management system." Expert Systems with Applications 29, no. 1 (July 2005): 219–28. http://dx.doi.org/10.1016/j.eswa.2005.01.017.

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Berdiyeva, Oguljan, Muhammad Umar Islam, and Mitra Saeedi. "Artificial Intelligence in Accounting and Finance: Meta-Analysis." Volume 3, Issue 1 3, no. 1 (July 31, 2021): 56–79. http://dx.doi.org/10.37435/nbr21032502.

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The use of the traditional system is declined greatly and with a modernization of the accounting and finance process there have been a great deal of change, and these improvements are beneficial to the accounting and finance industry. Adopting Artificial Intelligence applications such as Expert systems for audit and tax, Intelligent Agents for customer service, Machine Learning for decision making, etc. can lead a great benefit by reducing errors and increasing the efficiency of the accounting and finance processes. To keep ensuring a transparent and replicable process, we have conducted a meta-analysis. The database search was between the years 1989-2020 and reviewed 150 research papers. As meta-analysis results show, the majority of researches illustrate a positive effect of the impact of AI systems in the accounting and finance process. Key points:  Meta-Analysis has been applied for emphasizing positive results of the impact of Artificial Intelligence systems in the Accounting and Finance process.  Implementing Artificial Intelligence systems in Accounting and Finance process can increase the efficiency of the process.  Artificial Intelligence technology has been influential in all the areas of accounting, which are especially concerned with knowledge

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Chen, Te Fu. "Applying Artificial Intelligence in CRM: Case Studies of Intelligent Virtual Agents and Pegasystems." Applied Mechanics and Materials 182-183 (June 2012): 878–82. http://dx.doi.org/10.4028/www.scientific.net/amm.182-183.878.

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It is highly technical and specialized for AI research, and deeply divided into subfields that often fail to communicate with each other. Subfields have grown up around particular institutions, the work of individual researchers, the solution of specific problems, longstanding differences of opinion about how AI should be done and the application of widely differing tools. The central problems of AI include such traits as reasoning, knowledge, planning, learning, communication, perception and the ability to move and manipulate objects. Currently, in the form of applications of AI, is slowly making its way out of laboratories into the mainstream market. The study reviews AI and CRM, the evolution of CRM: XRM, the applications of AI in CRM including customer support automation, automated online assistant and online and telephone customer service. Finally, the study examines the applications of AI in CRM via two case studies of Intelligent Virtual Agents (IVAs) and Pegasystems to link the theories and practices.

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Quitadamo, Raffaele, and Franco Zambonelli. "Autonomic communication services: a new challenge for software agents." Autonomous Agents and Multi-Agent Systems 17, no. 3 (May 14, 2008): 457–75. http://dx.doi.org/10.1007/s10458-008-9054-9.

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Ogunbiyi, Niyi, Artie Basukoski, and Thierry Chaussalet. "An Exploration of Ethical Decision Making with Intelligence Augmentation." Social Sciences 10, no. 2 (February 8, 2021): 57. http://dx.doi.org/10.3390/socsci10020057.

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In recent years, the use of Artificial Intelligence agents to augment and enhance the operational decision making of human agents has increased. This has delivered real benefits in terms of improved service quality, delivery of more personalised services, reduction in processing time, and more efficient allocation of resources, amongst others. However, it has also raised issues which have real-world ethical implications such as recommending different credit outcomes for individuals who have an identical financial profile but different characteristics (e.g., gender, race). The popular press has highlighted several high-profile cases of algorithmic discrimination and the issue has gained traction. While both the fields of ethical decision making and Explainable AI (XAI) have been extensively researched, as yet we are not aware of any studies which have examined the process of ethical decision making with Intelligence augmentation (IA). We aim to address that gap with this study. We amalgamate the literature in both fields of research and propose, but not attempt to validate empirically, propositions and belief statements based on the synthesis of the existing literature, observation, logic, and empirical analogy. We aim to test these propositions in future studies.

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SÁNCHEZ-ANGUIX, VÍCTOR, SOLEDAD VALERO, and ANA GARCÍA-FORNES. "A GENETIC APPROACH FOR LONG TERM VIRTUAL ORGANIZATION DISTRIBUTION." International Journal on Artificial Intelligence Tools 20, no. 02 (April 2011): 271–95. http://dx.doi.org/10.1142/s0218213011000152.

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An agent-based Virtual Organization is a complex entity where dynamic collections of agents agree to share resources in order to accomplish a global goal or offer a complex service. An important problem for the performance of the Virtual Organization is the distribution of the agents across the computational resources. The final distribution should provide a good load balancing for the organization. In this article, a genetic algorithm is applied to calculate a proper distribution across hosts in an agent-based Virtual Organization. Additionally, an abstract multi-agent system architecture which provides infrastructure for Virtual Organization distribution is introduced. The developed genetic solution employs an elitist crossover operator where one of the children inherits the most promising genetic material from the parents with higher probability. In order to validate the genetic proposal, the designed genetic algorithm has been successfully compared to several heuristics in different scenarios.

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Jurca, R., and B. Faltings. "Mechanisms for Making Crowds Truthful." Journal of Artificial Intelligence Research 34 (March 17, 2009): 209–53. http://dx.doi.org/10.1613/jair.2621.

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We consider schemes for obtaining truthful reports on a common but hidden signal from large groups of rational, self-interested agents. One example are online feedback mechanisms, where users provide observations about the quality of a product or service so that other users can have an accurate idea of what quality they can expect. However, (i) providing such feedback is costly, and (ii) there are many motivations for providing incorrect feedback. Both problems can be addressed by reward schemes which (i) cover the cost of obtaining and reporting feedback, and (ii) maximize the expected reward of a rational agent who reports truthfully. We address the design of such incentive-compatible rewards for feedback generated in environments with pure adverse selection. Here, the correlation between the true knowledge of an agent and her beliefs regarding the likelihoods of reports of other agents can be exploited to make honest reporting a Nash equilibrium. In this paper we extend existing methods for designing incentive-compatible rewards by also considering collusion. We analyze different scenarios, where, for example, some or all of the agents collude. For each scenario we investigate whether a collusion-resistant, incentive-compatible reward scheme exists, and use automated mechanism design to specify an algorithm for deriving an efficient reward mechanism.

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Hioual, Ouassila, Ouided Hioual, Sofiane Mounine Hemam, Rania Mordjane, and Nessrine Bouhlala. "Fault Tolerance for Composite Cloud Services: A Novel Approach Based MAS." Inteligencia Artificial 25, no. 69 (June 15, 2022): 183–200. http://dx.doi.org/10.4114/intartif.vol25iss69pp183-200.

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Several Cloud services may be composed in order to respond quickly to the needs of users. Unfortunately, when running such a service some faults may occur. The outcome of fault control is a big challenge. In this paper, the authors propose a new approach based back recovery and multi-agent planning methods. The proposed architecture based MAS (Multi-Agent System) is composed of two main types of Agents : a Composition Manager Agent (CMA) and a Supervisor Agent (SA). The role of the CMA is to create a set of plans as an oriented graph where the nodes are the Cloud services and the valued arcs represent the composition order of these services. This agent saves checkpoints (nodes) in a stable memory so that there are at least one possible path. However, the SA ensures that the running plan is working properly; otherwise, it informs the CMA to select another sub-plan. Experimental results show the performance and effectiveness of the proposed approach.

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Milne-Ives, Madison, Caroline de Cock, Ernest Lim, Melissa Harper Shehadeh, Nick de Pennington, Guy Mole, Eduardo Normando, and Edward Meinert. "The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review." Journal of Medical Internet Research 22, no. 10 (October 22, 2020): e20346. http://dx.doi.org/10.2196/20346.

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Background The high demand for health care services and the growing capability of artificial intelligence have led to the development of conversational agents designed to support a variety of health-related activities, including behavior change, treatment support, health monitoring, training, triage, and screening support. Automation of these tasks could free clinicians to focus on more complex work and increase the accessibility to health care services for the public. An overarching assessment of the acceptability, usability, and effectiveness of these agents in health care is needed to collate the evidence so that future development can target areas for improvement and potential for sustainable adoption. Objective This systematic review aims to assess the effectiveness and usability of conversational agents in health care and identify the elements that users like and dislike to inform future research and development of these agents. Methods PubMed, Medline (Ovid), EMBASE (Excerpta Medica dataBASE), CINAHL (Cumulative Index to Nursing and Allied Health Literature), Web of Science, and the Association for Computing Machinery Digital Library were systematically searched for articles published since 2008 that evaluated unconstrained natural language processing conversational agents used in health care. EndNote (version X9, Clarivate Analytics) reference management software was used for initial screening, and full-text screening was conducted by 1 reviewer. Data were extracted, and the risk of bias was assessed by one reviewer and validated by another. Results A total of 31 studies were selected and included a variety of conversational agents, including 14 chatbots (2 of which were voice chatbots), 6 embodied conversational agents (3 of which were interactive voice response calls, virtual patients, and speech recognition screening systems), 1 contextual question-answering agent, and 1 voice recognition triage system. Overall, the evidence reported was mostly positive or mixed. Usability and satisfaction performed well (27/30 and 26/31), and positive or mixed effectiveness was found in three-quarters of the studies (23/30). However, there were several limitations of the agents highlighted in specific qualitative feedback. Conclusions The studies generally reported positive or mixed evidence for the effectiveness, usability, and satisfactoriness of the conversational agents investigated, but qualitative user perceptions were more mixed. The quality of many of the studies was limited, and improved study design and reporting are necessary to more accurately evaluate the usefulness of the agents in health care and identify key areas for improvement. Further research should also analyze the cost-effectiveness, privacy, and security of the agents. International Registered Report Identifier (IRRID) RR2-10.2196/16934

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El-Gohary, Hatem, Aksaya Thayaseelan, Simeon Babatunde, and Salma El-Gohary. "An Exploratory Study on the Effect of Artificial Intelligence-Enabled Technology on Customer Experiences in the Banking Sector." Journal of Technological Advancements 1, no. 1 (January 2021): 1–17. http://dx.doi.org/10.4018/jta.20210101.oa1.

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This study investigates how artificial intelligent technology in the banking sector has affected consumers’ overall experience. It focuses on how consumers’ personal digital transformation has affected digital banking development and how this further affects consumer’s expectations and experience. It assesses how banks use Artificial Intelligent Virtual Agents such as Chatbots to transform how consumers use their banking facilities. Lastly, this study investigates the scope of neobanks in the banking sector. The study found that digital transformations have led to an increase in consumers’ expectations from their banks. Whilst banks revolutionise their customer service offerings through virtual agents, customers are not engaging with these at an expected rate. Findings revealed that Neobanks are not operating at their expected traction due to consumer knowledge gaps, occasioned by a lack of advertised information to customers from their banks.

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Rieder, Travis N., Brian Hutler, and Debra J. H. Mathews. "Artificial Intelligence in Service of Human Needs: Pragmatic First Steps Toward an Ethics for Semi-Autonomous Agents." AJOB Neuroscience 11, no. 2 (March 31, 2020): 120–27. http://dx.doi.org/10.1080/21507740.2020.1740354.

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Aattouri, Imad, Hicham Mouncif, and Mohamed Rida. "Modeling of an artificial intelligence based enterprise callbot with natural language processing and machine learning algorithms." IAES International Journal of Artificial Intelligence (IJ-AI) 12, no. 2 (June 1, 2023): 943. http://dx.doi.org/10.11591/ijai.v12.i2.pp943-955.

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<p>The management of customer services by telephone encounters several problems: an uncontrollable flow of calls, complicated resource management, a very high cost of service, and more. Opportunities to improve the quality of service, save time and money triggered the widespread implementation of artificial intelligence (AI) based callbot. This article outlines the straightforward workflow developed to model the architecture of the callbot. Therefore, several algorithms were evaluated and compared based on real knowledge of a call center of an insurance society. The algorithms considered are: k-nearest neighbours (KNN), support vector machine (SVM), random forests (RF), logistic regression (LR), and Na¨ıve Bayes (NB). The comparison criteria are: correct responses, response time, accuracy, Cohen’s kappa and F1 score using n-gram (1.1) and (2.2). The results obtained show that the SVM (accuracy=70.29%) presents the best results on all the comparison criteria. The comparison between the results of the human agents and the callbot shows an improvement in several levels: the cost savings are greater than 80% on all the tests carried out, the holding time decrease to 0 seconds, and the processing time (almost a third or more). The results obtained sufficiently meet the objectives of this project.</p>

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Mudofi, Luthfi Nurul Hidayah, and Wardah Yuspin. "EVALUATING QUALITY OF CHATBOTS AND INTELLIGENT CONVERSATIONAL AGENTS OF BCA (VIRA) LINE." Interdisciplinary Social Studies 1, no. 5 (February 20, 2022): 532–42. http://dx.doi.org/10.55324/iss.v1i5.122.

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Background: The use of technology in the financial sector greatly supports its productivity. Including the use of Artificial Intelligence or Artificial Intelligence that makes activities in the financial sector faster and more efficient. PT. Bank Central Asia also implemented Artificial Intelligence technology by launching a chatbot feature called VIRA. Although this vira provides various conveniences this feature has a disadvantage of this feature is that the account can be accessed without using a pin, but only with a card number and OTP code. Aim: This research aims to look at the legal protection of the use of VIRA chatbots in BCA customers' banking activities. Method: This research is included in the type of empirical juridical legal research with library research and vira application observation. Findings: The results showed that BCA customers can only access personal data using VIRA. The main facilities of chatbot VIRA are more general information services and promotions for customers. In addition, the account is not automatically logged out, so when the phone is lost others may be able to access the account of the mobile phone owner through VIRA.

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De Keyser, Arne, Sarah Köcher, Linda Alkire (née Nasr), Cédric Verbeeck, and Jay Kandampully. "Frontline Service Technology infusion: conceptual archetypes and future research directions." Journal of Service Management 30, no. 1 (January 14, 2019): 156–83. http://dx.doi.org/10.1108/josm-03-2018-0082.

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PurposeSmart technologies and connected objects are rapidly changing the organizational frontline. Yet, our understanding of how these technologies infuse service encounters remains limited. Therefore, the purpose of this paper is to update existing classifications of Frontline Service Technology (FST) infusion. Moreover, the authors discuss three promising smart and connected technologies – conversational agents, extended reality (XR) and blockchain technology – and their respective implications for customers, frontline employees and service organizations.Design/methodology/approachThis paper uses a conceptual approach integrating existing work on FST infusion with artificial intelligence, robotics, XR and blockchain literature, while also building on insights gathered through expert interviews and focus group conversations with members of two service research centers.FindingsThe authors define FST and propose a set of FST infusion archetypes at the organizational frontline. Additionally, the authors develop future research directions focused on understanding how conversational agents, XR and blockchain technology will impact service.Originality/valueThis paper updates and extends existing classifications of FST, while paving the road for further work on FST infusion.

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Menczer, Filippo, Le-Shin Wu, and Ruj Akavipat. "Intelligent Peer Networks for Collaborative Web Search." AI Magazine 29, no. 3 (September 6, 2008): 35. http://dx.doi.org/10.1609/aimag.v29i3.2155.

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Collaborative query routing is a new paradigm for Web search that treats both established search engines and other publicly available indices as intelligent peer agents in a search network. The approach makes it transparent for anyone to build their own (micro) search engine, by integrating established Web search services, desktop search, and topical crawling techniques. The challenge in this model is that each of these agents must learn about its environment— the existence, knowledge, diversity, reliability, and trustworthiness of other agents — by analyzing the queries received from and results exchanged with these other agents. We present the 6S peer network, which uses machine learning techniques to learn about the changing query environment. We show that simple reinforcement learning algorithms are sufficient to detect and exploit semantic locality in the network, resulting in efficient routing and high-quality search results. A prototype of 6S is available for public use and is intended to assist in the evaluation of different AI techniques employed by the networked agents.

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Ivaschenko, Anton, Alfiya R. Diyazitdinova, and Tatiyana Nikiforova. "Optimisation of the rational proportion of intelligent technologies application in service organisations." Organizacija 54, no. 2 (May 1, 2021): 162–77. http://dx.doi.org/10.2478/orga-2021-0011.

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Abstract Background and Purpose: The growing role and involvement of Artificial Intelligence in modern digital enterprises leads to a considerable reduction of personnel and reorientation of the remaining staff to new responsibilities. However, in many areas like services and support the total elimination of the employed human resources still remains impossible. It is proposed to study the organisational problem of finding the optimal proportion of computer agents and human actors in the mixed collaborative environment. Methods: Using the technology of semantic and statistical analysis, we developed an original model of computer agents’ and human actors’ cooperative interaction and an optimization method, which is novel in considering the focus of the executors while calculating the compliance indicators. Results: The problem was studied by an example of service desk automation. Considering the semantics of the problem domain in the form of ontology introduces the logic for better distribution and automation of tasks. Conclusion: In a modern digital enterprise there exists and can be estimated a rational balance between the computer agents and human actors, which becomes a significant indicator of its performance. In general, human actors are preferable for processing unpredictable events in real time, while agents are better at the modelling and simulation.

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BRIAN BLAKE, M. "AGENT-BASED COMMUNICATION FOR DISTRIBUTED WORKFLOW MANAGEMENT USING JINI TECHNOLOGIES." International Journal on Artificial Intelligence Tools 12, no. 01 (March 2003): 81–99. http://dx.doi.org/10.1142/s0218213003001125.

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Agent communication has developed widely over the past decade for various types of multiple agent environments. Originally, most of this research surrounded simulation systems and inference systems. Subsequently, agents are expected to adapt to, dynamically create, and understand evolving conversation policies. This concept of agent communication is not completely necessary in some domains. One such domain is that of distributed workflow management with implications into Electronic Commerce. In this domain, agents are "middle-agents" that represent the distributed components that implement each individual workflow step. By representing the component-based services of each step, multiple distributed agents can essentially manage a workflow or supply chain that spans several online businesses (B2B). The WARP (Workflow-Automation through Agent-Based Reflective Processes) architecture is a multi-agent architecture developed to support distributed workflow management environments where distributed components are used to implement each of the workflow steps This paper describes an object-oriented workflow ontology for this distributed workflow management domain. There is also a software engineering process for integrating new component-based services into this ontology. Furthermore, the interaction protocol and supporting implementation based on the Knowledge Query and Manipulation Language (KQML) are presented. This agent communication architecture is implemented using Sun MicroSystems' Java and Jini technologies.

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Huh, Jiwon, Soyoung Ann, Jeeyeon Hong, Mingzhu Cui, Ji Yeon Park, Yoonseo Kim, Bomin Sim, and Hyun-Kyung Lee. "Service Design of Artificial Intelligence Voice Agents as a Guideline for Assisting Independent Toilet Training of Preschool Children." Archives of Design Research 35, no. 3 (August 31, 2022): 81–93. http://dx.doi.org/10.15187/adr.2022.08.35.3.81.

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Spatola, Nicolas, and Karl F. Macdorman. "Why Real Citizens Would Turn to Artificial Leaders." Digital Government: Research and Practice 2, no. 3 (July 2021): 1–24. http://dx.doi.org/10.1145/3447954.

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Governments are increasingly using artificial intelligence to improve workflows and services. Applications range from predicting climate change, crime, and earthquakes to flu outbreaks, low air quality, and tax fraud. Artificial agents are already having an impact on eldercare, education, and open government, enabling users to complete procedures through a conversational interface. Whether replacing humans or assisting them, they are the technological fix of our times. In two experiments and a follow-up study, we investigate factors that influence the acceptance of artificial agents in positions of power, using attachment theory and disappointment theory as explanatory models. We found that when the state of the world provokes anxiety, citizens perceive artificial agents as a reliable proxy to replace human leaders. Moreover, people accept artificial agents as decision-makers in politics and security more willingly when they deem their leaders or government to be untrustworthy, disappointing, or immoral. Finally, we discuss these results with respect to theories of technology acceptance and the delegation of duties and prerogatives.

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TERASAKI, Tatsuya, Takeshi NAKAIDO, Takahiro KAWAMURA, Akihiko OHSUGA, and Mamoru MAEKAWA. "Development of Middle Agents Mediating Ubiquitous Environment and Web Services." Transactions of the Japanese Society for Artificial Intelligence 19 (2004): 343–50. http://dx.doi.org/10.1527/tjsai.19.343.

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Alechina, Natasha, Joseph Y. Halpern, Ian A. Kash, and Brian Logan. "Incentive-Compatible Mechanisms for Norm Monitoring in Open Multi-Agent Systems." Journal of Artificial Intelligence Research 62 (June 30, 2018): 433–58. http://dx.doi.org/10.1613/jair.1.11214.

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We consider the problem of detecting norm violations in open multi-agent systems (MAS). We show how, using ideas from scrip systems, we can design mechanisms where the agents comprising the MAS are incentivised to monitor the actions of other agents for norm violations. The cost of providing the incentives is not borne by the MAS and does not come from fines charged for norm violations (fines may be impossible to levy in a system where agents are free to leave and rejoin again under a different identity). Instead, monitoring incentives come from (scrip) fees for accessing the services provided by the MAS. In some cases, perfect monitoring (and hence enforcement) can be achieved: no norms will be violated in equilibrium. In other cases, we show that, while it is impossible to achieve perfect enforcement, we can get arbitrarily close; we can make the probability of a norm violation in equilibrium arbitrarily small. We show using simulations that our theoretical results, which apply to systems with a large number of agents, hold for multi-agent systems with as few as 1000 agents–the system rapidly converges to the steady-state distribution of scrip tokens necessary to ensure monitoring and then remains close to the steady state.

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Vetrò, Antonio, Antonio Santangelo, Elena Beretta, and Juan Carlos De Martin. "AI: from rational agents to socially responsible agents." Digital Policy, Regulation and Governance 21, no. 3 (May 13, 2019): 291–304. http://dx.doi.org/10.1108/dprg-08-2018-0049.

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Purpose This paper aims to analyze the limitations of the mainstream definition of artificial intelligence (AI) as a rational agent, which currently drives the development of most AI systems. The authors advocate the need of a wider range of driving ethical principles for designing more socially responsible AI agents. Design/methodology/approach The authors follow an experience-based line of reasoning by argument to identify the limitations of the mainstream definition of AI, which is based on the concept of rational agents that select, among their designed actions, those which produce the maximum expected utility in the environment in which they operate. The problem of biases in the data used by AI is taken as example, and a small proof of concept with real datasets is provided. Findings The authors observe that biases measurements on the datasets are sufficient to demonstrate potential risks of discriminations when using those data in AI rational agents. Starting from this example, the authors discuss other open issues connected to AI rational agents and provide a few general ethical principles derived from the White Paper AI at the service of the citizen, recently published by Agid, the agency of the Italian Government which designs and monitors the evolution of the IT systems of the Public Administration. Originality/value The paper contributes to the scientific debate on the governance and the ethics of AI with a critical analysis of the mainstream definition of AI.

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He, Qiang, Jun Yan, Ryszard Kowalczyk, Hai Jin, and Yun Yang. "Lifetime service level agreement management with autonomous agents for services provision." Information Sciences 179, no. 15 (July 2009): 2591–605. http://dx.doi.org/10.1016/j.ins.2009.01.037.

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BODANESE, ELIANE L., and LAURIE G. CUTHBERT. "APPLYING INTELLIGENT SOFTWARE AGENTS IN A DISTRIBUTED CHANNEL ALLOCATION SCHEME FOR CELLULAR NETWORKS." International Journal of Pattern Recognition and Artificial Intelligence 16, no. 08 (December 2002): 1021–39. http://dx.doi.org/10.1142/s0218001402002131.

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As the demand for mobile services has increased, the need for an efficient allocation of channels is essential to ensure good performance, given the limited spectrum available. Techniques for increasing flexibility in radio resource acquisition are needed to handle the heterogeneity of services and bit rates to be supported in the forthcoming generations of mobile communications. To improve the performance and efficiency of the channel allocation, we propose the use of a particular agent architecture that allows base stations to be more flexible and intelligent, including planning to attempt to balance the load in advance of reactive requests. The simulation results prove that the use of intelligent agents controlling the allocation of channels is feasible and the agent negotiation is an important feature of the system in order to improve perceived quality of service and to improve the load balancing of the traffic.

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CAO, J., J. WANG, S. ZHANG, and M. LI. "A dynamically reconfigurable system based on workflow and service agents." Engineering Applications of Artificial Intelligence 17, no. 7 (October 2004): 771–82. http://dx.doi.org/10.1016/s0952-1976(04)00115-0.

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DAVIDSSON, PAUL, and FREDRIK WERNSTEDT. "A multi-agent system architecture for coordination of just-in-time production and distribution." Knowledge Engineering Review 17, no. 4 (December 2002): 317–29. http://dx.doi.org/10.1017/s0269888903000560.

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A multi-agent system architecture for coordination of just-in-time production and distribution is presented. The problem to solve is twofold: first the right amount of resources at the right time should be produced, then these resources should be distributed to the right consumers. In order to solve the first problem, which is hard when the production and/or distribution time is relatively long, each consumer is equipped with an agent that makes predictions of future needs that it sends to a production agent. The second part of the problem is approached by forming clusters of consumers within which it is possible to redistribute resources fast and at a low cost in order to cope with discrepancies between predicted and actual consumption. Redistribution agents are introduced (one for each cluster) to manage the redistribution of resources. The suggested architecture is evaluated in a case study concerning management of district heating systems. Results from a simulation study show that the suggested approach makes it possible to control the trade-off between quality of service and degree of surplus production. We also compare the suggested approach to a reference control scheme (approximately corresponding to the current approach to district heating management), and conclude that it is possible to reduce the amount of resources produced while maintaining the quality of service. Finally, we describe a simulation experiment where the relation between the size of the clusters and the quality of service was studied.

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Mrozek, Mirosław. "Multi-Agent Control System for the Movement of Uniaxial Objects." Solid State Phenomena 237 (August 2015): 183–88. http://dx.doi.org/10.4028/www.scientific.net/ssp.237.183.

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Multi-agent systems are used mainly in IT solutions and control groups of robots. From the point of view of classical control architectures, they are a kind of distributed systems in which nodes perform advanced algorithms, usually associated with the technology of artificial intelligence, and they can be considered as agents. The article describes the multi-agents control system of objects of uniaxial movements. An example of such a system to control a repository with movable racks with electric motors is presented. Each rack acts as an agent through the implemented control of the resources of embedded microcontrollers. Such a system provides high quality control, guaranteeing long-lasting, trouble-free operation while maintaining the safety of both service and stored items.

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Бождай, Александр, Aleksandr Bozhday, Александр Бершадский, Aleksandr Bershadskiy, Вардан Мкртчан, and Vardan Mkrtchan. "Knowledge management methods in next-generation E/U Learning systems." Russian Journal of Management 3, no. 4 (August 31, 2015): 352–60. http://dx.doi.org/10.12737/13099.

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The article discusses the methods of knowledge management for E/U-Learning systems, which will provide the opportunities for the construction of a unified all-pervasive electronic educational environment. Authors analyze the development of a new phase of e-learning (E-Learning 3.0) in which will play an important role distributed computer systems, cloud computing, mobile personal devices and wireless networks, artificial intelligence and virtual reality tools. Today, there is a fundamental scientific problem of creating a unified interstate intellectual environment for e-education services. This environment should include heterogeneous forms of knowledge representation, interstate standards and forms of learning, international faculty and student teams. The article suggests a possible knowledge management methods and the approach to the construction of an all-pervading intellectual environment for e-learning services. The proposed approach is based on the integration of multiple technologies, such as: service-oriented design, engineering of DSPL (Dynamic Software Product Lines), wireless telecommunications, interaction of intelligent e-learning agents. Structural basis of this approach is interconnected pair of intelligent software agents: student’s and teacher’s software agents. These agents are able to adapt itself: to the current level of student’s knowledge; to the available software, hardware and network equipment; to the current demands of the environment (e.g. labor markets); to the modern educational standards. As a basis of software agents self-adaptation is a mathematical variability model, including the three basic features hierarchy: educational content, interface, software and technical support. Application of such variability model does not require recompilation of the source code (to make changes in the agents properties) and allows to organize a continuous process of e-learning and significantly increase the life cycle of the entire system of distance learning. Moreover, the authors propose a service-oriented scheme for knowledge flows management. The article will be useful for experts in e-learning, developers of service-oriented systems and for managers in the field of socio-economic systems.

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Xiaodong, Yang, Cui Weihong, Yang Hao, Li Cunjun, Huang Wenjiang, and Jihua Wang. "Integrating Geospatial Web Services Into Enterprise Business System based on Service Intelligent Agents and Bayesian Network." Intelligent Automation & Soft Computing 17, no. 6 (January 2011): 701–11. http://dx.doi.org/10.1080/10798587.2011.10643180.

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Asaad, Renas Rajab, Veman Ashqi Saeed, and Revink Masud Abdulhakim. "Smart Agent and it’s effect on Artificial Intelligence : A Review Study." ICONTECH INTERNATIONAL JOURNAL 5, no. 4 (December 28, 2021): 1–9. http://dx.doi.org/10.46291/icontechvol5iss4pp1-9.

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Current networking technologies, as well as the ready availability of large quantities of data and knowledge on the Internet-based Infosphere, offer tremendous opportunities for providing more abundant and reliable information to decision makers and decision support systems. The use of the Internet has increased at a breakneck pace. Some prevailing features of the Infosphere, however, have hindered successful use of the Internet by humans or decision support machine systems. To begin with, the information available on the internet is disorganized, multi-modal, and spread around the globe on server pages. Second, every day, the number and variety of data sources and services grows dramatically. In addition, the availability, type, and dependability of information services are all changing all the time. Third, the same piece of knowledge can be obtained from a number of different sources. Fourth, due to the complex existence of information sources and possible information updating and maintenance issues, information is vague and probably incorrect. As a result, collecting, filtering, evaluating, and using information in problem solving is becoming increasingly difficult for a human or computer device. As a consequence, identifying information sources, accessing, filtering, and incorporating data in support of decision-making, as well as managing information retrieval and problem-solving efforts of information sources and decision-making processes, has become a critical challenge. To fix this issue, the idea of "Intelligent Software Agents" has been suggested. Although a precise definition of an intelligent agent is still a work in progress, the current working definition is that Intelligent Software Agents are programs that act on behalf of their human users to perform laborious information gathering tasks such as locating and accessing information from various on-line information sources, resolving inconsistencies in the retrieved information, filtering out irrelevant data.

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Belda-Medina, Jose, and José Ramón Calvo-Ferrer. "Using Chatbots as AI Conversational Partners in Language Learning." Applied Sciences 12, no. 17 (August 24, 2022): 8427. http://dx.doi.org/10.3390/app12178427.

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Recent advances in Artificial Intelligence (AI) and machine learning have paved the way for the increasing adoption of chatbots in language learning. Research published to date has mostly focused on chatbot accuracy and chatbot–human communication from students’ or in-service teachers’ perspectives. This study aims to examine the knowledge, level of satisfaction and perceptions concerning the integration of conversational AI in language learning among future educators. In this mixed method research based on convenience sampling, 176 undergraduates from two educational settings, Spain (n = 115) and Poland (n = 61), interacted autonomously with three conversational agents (Replika, Kuki, Wysa) over a four-week period. A learning module about Artificial Intelligence and language learning was specifically designed for this research, including an ad hoc model named the Chatbot–Human Interaction Satisfaction Model (CHISM), which was used by teacher candidates to evaluate different linguistic and technological features of the three conversational agents. Quantitative and qualitative data were gathered through a pre-post-survey based on the CHISM and the TAM2 (technology acceptance) models and a template analysis (TA), and analyzed through IBM SPSS 22 and QDA Miner software. The analysis yielded positive results regarding perceptions concerning the integration of conversational agents in language learning, particularly in relation to perceived ease of use (PeU) and attitudes (AT), but the scores for behavioral intention (BI) were more moderate. The findings also unveiled some gender-related differences regarding participants’ satisfaction with chatbot design and topics of interaction.

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KARAGEORGOS, ANTHONY, NIKOLAY MEHANDJIEV, and SIMON THOMPSON. "RAMASD: a semi-automatic method for designing agent organisations." Knowledge Engineering Review 17, no. 4 (December 2002): 331–58. http://dx.doi.org/10.1017/s0269888903000572.

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Designing realistic multi-agent systems is a complex process, which involves specifying not only the functionality of individual agents, but also the authority relationships and lines of communication existing among them. In other words, designing a multi-agent system refers to designing an agent organisation. Existing methodologies follow a wide variety of approaches to designing agent organisations, but they do not provide adequate support for the decisions involved in moving from analysis to design. Instead, they require designers to make ad hoc design decisions while working at a low level of abstraction.We have developed RAMASD (Role Algebraic Multi-Agent System Design), a method for semi-automatic design of agent organisations based on the concept of role models as first-class design constructs. Role models represent agent behaviour, and the design of the agent system is done by systematically allocating roles to agents. The core of this method is a formal model of basic relations between roles, which we call role algebra. The semantics of this role-relationships model are formally defined using a two-sorted algebra.In this paper, we review existing agent system design methodologies to highlight areas where further work is required, describe how our method can address some of the outstanding issues and demonstrate its application to a case study involving telephone repair service teams.

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Nadarzynski, Tom, Vannesa Puentes, Izabela Pawlak, Tania Mendes, Ian Montgomery, Jake Bayley, and Damien Ridge. "Barriers and facilitators to engagement with artificial intelligence (AI)-based chatbots for sexual and reproductive health advice: a qualitative analysis." Sexual Health 18, no. 5 (2021): 385. http://dx.doi.org/10.1071/sh21123.

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Background The emergence of artificial intelligence (AI) provides opportunities for demand management of sexual and reproductive health services. Conversational agents/chatbots are increasingly common, although little is known about how this technology could aid services. This study aimed to identify barriers and facilitators for engagement with sexual health chatbots to advise service developers and related health professionals. Methods In January–June 2020, we conducted face-to-face, semi-structured and online interviews to explore views on sexual health chatbots. Participants were asked to interact with a chatbot, offering advice on sexually transmitted infections (STIs) and relevant services. Participants were UK-based and recruited via social media. Data were recorded, transcribed verbatim and analysed thematically. Results Forty participants (aged 18–50 years; 64% women, 77% heterosexual, 58% white) took part. Many thought chatbots could aid sex education, providing useful information about STIs and sign-posting to sexual health services in a convenient, anonymous and non-judgemental way. Some compared chatbots to health professionals or Internet search engines and perceived this technology as inferior, offering constrained content and interactivity, limiting disclosure of personal information, trust and perceived accuracy of chatbot responses. Conclusions Despite mixed attitudes towards chatbots, this technology was seen as useful for anonymous sex education but less suitable for matters requiring empathy. Chatbots may increase access to clinical services but their effectiveness and safety need to be established. Future research should identify which chatbots designs and functions lead to optimal engagement with this innovation.

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JONG, STEVEN DE, KARL TUYLS, and KATJA VERBEECK. "Fairness in multi-agent systems." Knowledge Engineering Review 23, no. 2 (June 2008): 153–80. http://dx.doi.org/10.1017/s026988890800132x.

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AbstractMulti-agent systems are complex systems in which multiple autonomous entities, called agents, cooperate in order to achieve a common or personal goal. These entities may be computer software, robots, and also humans. In fact, many multi-agent systems are intended to operate in cooperation with or as a service for humans. Typically, multi-agent systems are designed assuming perfectly rational, self-interested agents, according to the principles of classical game theory. Recently, such strong assumptions have been relaxed in various ways. One such way is explicitly including principles derived from human behavior. For instance, research in the field of behavioral economics shows that humans are not purely self-interested. In addition, they strongly care aboutfairness. Therefore, multi-agent systems that fail to take fairness into account, may not be sufficiently aligned with human expectations and may not reach intended goals. In this paper, we present an overview of work in the area of fairness in multi-agent systems. More precisely, we first look at the classical agent model, that is, rational decision making. We then provide an outline of descriptive models of fairness, that is, models that explain how and why humans reach fair decisions. Then, we look at prescriptive, computational models for achieving fairness in adaptive multi-agent systems. We show that results obtained by these models are compatible with experimental and analytical results obtained in the field of behavioral economics.

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Merz, M., and W. Lamersdorf. "Crossing Organizational Boundaries with Mobile Agents in Electronic Service Markets." Integrated Computer-Aided Engineering 6, no. 2 (April 1, 1999): 91–104. http://dx.doi.org/10.3233/ica-1999-6201.

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Journal articles on the topic 'Artificial intelligence service agents'

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