Academic literature on the topic 'General-purpose agent'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'General-purpose agent.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "General-purpose agent":
Lu, Cewu, and Shiquan Wang. "The General-Purpose Intelligent Agent." Engineering 6, no. 3 (March 2020): 221–26. http://dx.doi.org/10.1016/j.eng.2019.12.013.
Kohjiya, Shinzo, and Yuko Ikeda. "Reinforcement of General-Purpose Grade Rubbers by Silica Generated In Situ." Rubber Chemistry and Technology 73, no. 3 (July 1, 2000): 534–50. http://dx.doi.org/10.5254/1.3547604.
Fakhi, Hicham, Omar Bouattane, Mohamed Youssfi, and Hassan Ouajji. "A multi-agent model for general-purpose computing on graphics processing units." Multiagent and Grid Systems 13, no. 3 (September 28, 2017): 237–52. http://dx.doi.org/10.3233/mgs-170269.
Rojas, Eddy M., and Amlan Mukherjee. "Multi-Agent Framework for General-Purpose Situational Simulations in the Construction Management Domain." Journal of Computing in Civil Engineering 20, no. 3 (May 2006): 165–76. http://dx.doi.org/10.1061/(asce)0887-3801(2006)20:3(165).
Anchekov, M. I., A. Z. Apshev, K. Ch Bzhikhatlov, S. A. Kankulov, Z. V. Nagoev, O. V. Nagoeva, and I. A. Pshenokova. "Principles of ontophylogenetic development of artificial general intelligence systems based on multi-agent neurocognitive architectures." BIO Web of Conferences 84 (2024): 02015. http://dx.doi.org/10.1051/bioconf/20248402015.
Yoshida, Naoto. "Homeostatic Agent for General Environment." Journal of Artificial General Intelligence 8, no. 1 (March 7, 2018): 1–22. http://dx.doi.org/10.1515/jagi-2017-0001.
Tian, Xue Yong, Tian Qing Chang, Shao Hua Shi, Lei Zhang, and Yang Han. "Modeling of Test Resource Based on Multi-Agent and its Application in Intelligent Virtual Instrument." Advanced Materials Research 139-141 (October 2010): 1973–76. http://dx.doi.org/10.4028/www.scientific.net/amr.139-141.1973.
Feng, Yongxin, Guangjie Han, Nan Bai, and Wenbo Zhang. "Design and implementation of a CATV network management system based on a general-purpose agent." International Journal of Autonomous and Adaptive Communications Systems 12, no. 4 (2019): 285. http://dx.doi.org/10.1504/ijaacs.2019.10025317.
Zhang, Wenbo, Nan Bai, Guangjie Han, and Yongxin Feng. "Design and implementation of a CATV network management system based on a general-purpose agent." International Journal of Autonomous and Adaptive Communications Systems 12, no. 4 (2019): 285–98. http://dx.doi.org/10.1504/ijaacs.2019.103670.
LAHOTI, DEEPAK, ASEEM BHATNAGAR, AJAY K. SINGH, SUMATI SUNDARAIYA, KISHAN SAWROOP, and THAKURI SINGH. "Tc-99m Dextran: A New and Sensitive General Purpose Scintigraphic Agent for Diagnosing Intestinal Inflammation." Clinical Nuclear Medicine 24, no. 6 (June 1999): 424–27. http://dx.doi.org/10.1097/00003072-199906000-00010.
Dissertations / Theses on the topic "General-purpose agent":
Zabel, Martin, Thomas B. Preußer, Peter Reichel, and Rainer G. Spallek. "SHAP-Secure Hardware Agent Platform." Universitätsbibliothek Chemnitz, 2007. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200701011.
Gallouedec, Quentin. "Toward the generalization of reinforcement learning." Electronic Thesis or Diss., Ecully, Ecole centrale de Lyon, 2024. http://www.theses.fr/2024ECDL0013.
Conventional Reinforcement Learning (RL) involves training a unimodal agent on a single, well-defined task, guided by a gradient-optimized reward signal. This framework does not allow us to envisage a learning agent adapted to real-world problems involving diverse modality streams, multiple tasks, often poorly defined, sometimes not defined at all. Hence, we advocate for transitioning towards a more general framework, aiming to create RL algorithms that more inherently versatile.To advance in this direction, we identify two primary areas of focus. The first aspect involves improving exploration, enabling the agent to learn from the environment with reduced dependence on the reward signal. We present Latent Go-Explore (LGE), an extension of the Go-Explore algorithm. While Go-Explore achieved impressive results, it was constrained by domain-specific knowledge. LGE overcomes these limitations, offering wider applicability within a general framework. In various tested environments, LGE consistently outperforms the baselines, showcasing its enhanced effectiveness and versatility. The second focus is to design a general-purpose agent that can operate in a variety of environments, thus involving a multimodal structure and even transcending the conventional sequential framework of RL. We introduce Jack of All Trades (JAT), a multimodal Transformer-based architecture uniquely tailored to sequential decision tasks. Using a single set of weights, JAT demonstrates robustness and versatility, competing its unique baseline on several RL benchmarks and even showing promising performance on vision and textual tasks. We believe that these two contributions are a valuable step towards a more general approach to RL. In addition, we present other methodological and technical advances that are closely related to our core research question. The first is the introduction of a set of sparsely rewarded simulated robotic environments designed to provide the community with the necessary tools for learning under conditions of low supervision. Notably, three years after its introduction, this contribution has been widely adopted by the community and continues to receive active maintenance and support. On the other hand, we present Open RL Benchmark, our pioneering initiative to provide a comprehensive and fully tracked set of RL experiments, going beyond typical data to include all algorithm-specific and system metrics. This benchmark aims to improve research efficiency by providing out-of-the-box RL data and facilitating accurate reproducibility of experiments. With its community-driven approach, it has quickly become an important resource, documenting over 25,000 runs.These technical and methodological advances, along with the scientific contributions described above, are intended to promote a more general approach to Reinforcement Learning and, we hope, represent a meaningful step toward the eventual development of a more operative RL agent
Tripodi, Sébastien. "Étude de l'auto-organisation des cellules basées sur le Modèle de Potts Cellulaire." Brest, 2011. http://www.theses.fr/2011BRES2068.
The self-organization between the cells gives an explanation of the cell tissues morphogenesis, like the phenomenon of embryogenesis. Meanwhile, there is no consensus on the nature of the interactions between the cells leading to this self-organization. On one hand, the in silico modelisation and simulation offers a formal support to help the biologist in his understanding of the phenomenon and gives arguments in favor of a theory or of another one. The computer science implementation of biological process allows, on the other hand, improving the existing computer science models. The multi-agent systems are computer science models which represent each entity (agent) of a system in an explicit way. The agents are executed in an autonomous way and in interaction with the others. Cell agents can be simulated with a multi-agent system, where interactions are based on the consumption and production of molecules, but also on the adhesion and pressure cells exert on each other. A cell agent is based on the cell defined in the Cellular Potts Model. This model has been extended (MorphoPotts) in order to allow the cells to reach a generic and dynamic shape and to define an energy balance. The theory of Darwin at cellular level, an original theory of the embryogenesis, has been simulated via MorphoPotts where tissues emerge from one stem cell. These tissues are coherent because they have a continue renewal and a recognizable shape. To verify if the interactions between the MorphoPotts allow the system to self-organize and self-adapt, the performances of the multi-agent systems were enhanced. We show that the graphics processing unit (GPU) programming leads to considerable performance gains. The simulations done on the OPU show that a cellular darwinism allows the cell tissue to self-organize and self-adapt in reply to exterior events
Ekron, Kieron Charles. "A distributed, multi-agent model for general purpose crowd simulation." Thesis, 2012. http://hdl.handle.net/10210/8119.
The purpose of the research presented in this dissertation is to explore the use of a distributed multi-agent system in a general purpose crowd simulation model. Crowd simulation is becoming an increasingly important tool for analysing new construction projects, as it enables safety and performance evaluations to be performed on architectural plans before the buildings have been constructed. Crowd simulation is a challenging problem, as it requires the simulation of complex interactions of people within a crowd. The dissertation investigates existing models of crowd simulation and identifies three primary sub-tasks of crowd simulation: deliberation, path planning and collision-avoiding movement. Deliberation is the process of determining which goal an agent will attempt to satisfy next. Path planning is the process of finding a collision-free path from an agent‟s current location towards its goal. Collision-avoiding movement deals with moving an agent along its calculated path while avoiding collisions with other agents. A multi-agent crowd simulation model, DiMACS, is proposed as a means of addressing the problem of crowd simulation. Multi-agent technology provides an effective solution for representing individuals within a crowd; each member of a crowd can be represented as an intelligent agent. Intelligent agents are capable of maintaining their own internal state and deciding on a course of action based on that internal state. DiMACS is capable of producing realistic simulations while making use of distributed and parallel processing to improve its performance. In addition, the model is highly customisable. The dissertation also presents a user-friendly method for configuring agents within a simulation that abstracts the complexity of agent behaviour away from a user so as to increase the accessibility of configuring the proposed model. In addition, an application programming interface is provided that enables developers to extend the model to simulate additional agent behaviours. The research shows how distributed and parallel processing may be used to improve the performance of an agent-based crowd simulation without compromising the accuracy of the simulation.
Wu, Lin-Yu, and 吳苓諭. "Design of General-Purpose Cross-Linking Agents for Conjugation between a Protein and mall Molecules." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/xu83n3.
國立中興大學
化學系所
99
Chemical cross-linking of biological components is a recent outgrowth of chemical modification of proteins. The general approach for the labeling of proteins with small organic molecules involves the synthesis of a chemically reactive analog of the desired structure followed by reaction with the protein of interest. We design a reaction for conjugating the fluorescent molecule (2-naphthol) to a protein by several cross-linkers, such as 2-Iminothiolane (2-IT), p-Maleimidophenyl Isocynate (PMPI), succinic anhydride, and glutaric anhydride. We found that 2-IT is a useful coupling reagent, which is capable of reacting with the side chains of residues in a protein. The succinic anhydride and glutaric anhydride are used because they can be relatively easy to obtain, and can form the chemical bonding between the reactive amino acid side chains in proteins and fluorescent molecules.
Books on the topic "General-purpose agent":
Matthews, George R. Zebulon Pike. ABC-CLIO, LLC, 2016. http://dx.doi.org/10.5040/9798216040231.
Kashiwagi, Helena Midori, Maurício Cesar Vitória Fagundes, and Luciane Godoy Bonafini. Formação de agentes ambientais mirins: Protocolo de aplicação de atividades de educação ambiental para professores da educação do campo. Brazil Publishing, 2021. http://dx.doi.org/10.31012/978-65-5861-386-2.
Book chapters on the topic "General-purpose agent":
Iglesias, Carlos A., José C. González, and Juan R. Velasco. "MIX: A general purpose multiagent architecture." In Intelligent Agents II Agent Theories, Architectures, and Languages, 251–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3540608052_71.
Sánchez, David, David Isern, Ángel Rodríguez, and Antonio Moreno. "General Purpose Agent-Based Parallel Computing." In Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living, 232–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02481-8_33.
Ciatto, Giovanni, Matteo Magnini, Berk Buzcu, Reyhan Aydoğan, and Andrea Omicini. "A General-Purpose Protocol for Multi-agent Based Explanations." In Explainable and Transparent AI and Multi-Agent Systems, 38–58. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-40878-6_3.
Rodríguez, Aarón, and Luis Castillo. "A First Step Towards a General-Purpose Distributed Cyberdefense System." In Advances in Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection, 237–47. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94580-4_19.
Jonker, Catholijn M., Reyhan Aydoğan, Tim Baarslag, Joost Broekens, Christian A. Detweiler, Koen V. Hindriks, Alina Huldtgren, and Wouter Pasman. "An Introduction to the Pocket Negotiator: A General Purpose Negotiation Support System." In Multi-Agent Systems and Agreement Technologies, 13–27. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59294-7_2.
Feng, Wei, Yu Qin, Dengguo Feng, Ge Wei, Lihui Xue, and Dexian Chang. "Mobile Trusted Agent (MTA): Build User-Based Trust for General-Purpose Computer Platform." In Network and System Security, 307–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38631-2_23.
Albanese, Giuseppe, Davide Calvaresi, Paolo Sernani, Fabien Dubosson, Aldo Franco Dragoni, and Michael Schumacher. "MAXIM-GPRT: A Simulator of Local Schedulers, Negotiations, and Communication for Multi-Agent Systems in General-Purpose and Real-Time Scenarios." In Advances in Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection, 291–95. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94580-4_23.
Ekron, Kieron, Jaco Bijker, and Elize Ehlers. "Reducing the Environmental Impact of New Construction Projects through General Purpose Building Design and Multi-agent Crowd Simulation." In Lecture Notes in Computer Science, 460–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25044-6_37.
Potapov, Alexey, Anatoly Belikov, Oleg Scherbakov, and Vitaly Bogdanov. "General-Purpose Minecraft Agents and Hybrid AGI." In Artificial General Intelligence, 75–85. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-19907-3_8.
Salcido, Gustavo Julio Puente, and Eduardo César Contreras Delgado. "Intelligent Agent to Identify Rheumatic Diseases." In Handbook of Research on ICTs and Management Systems for Improving Efficiency in Healthcare and Social Care, 451–73. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-3990-4.ch023.
Conference papers on the topic "General-purpose agent":
Streeter, Tyler, James Oliver, and Adrian Sannier. "Verve: A General Purpose Open Source Reinforcement Learning Toolkit." In ASME 2006 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/detc2006-99651.
Rodriguez, Sebastian, Nicolas Gaud, and Stephane Galland. "SARL: A General-Purpose Agent-Oriented Programming Language." In 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT). IEEE, 2014. http://dx.doi.org/10.1109/wi-iat.2014.156.
Nardini, Elena, Andrea Omicini, and Mirko Viroli. "General-Purpose Coordination Abstractions for Managing Interaction in MAS." In 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology. IEEE, 2009. http://dx.doi.org/10.1109/wi-iat.2009.335.
Lavendelis, Egons. "Extending the MASITS Methodology for General Purpose Agent Oriented Software Engineering." In International Conference on Agents and Artificial Intelligence. SCITEPRESS - Science and and Technology Publications, 2015. http://dx.doi.org/10.5220/0005202201570165.
Ricci, Alessandro, and Andrea Santi. "Designing a general-purpose programming language based on agent-oriented abstractions." In the compilation of the co-located workshops. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2095050.2095078.
Hongjin Liu, Bin Yuan, Hongwei Dai, Jikeng Lin, and Y. X. Ni. "Framework design of a general-purpose power market simulator based on multi-agent technology." In Proceedings of Power Engineering Society Summer Meeting. IEEE, 2001. http://dx.doi.org/10.1109/pess.2001.970294.
Guo, Xu, Han Yu, Chunyan Miao, and Yiqiang Chen. "Agent-based Decision Support for Pain Management in Primary Care Settings." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/943.
Belousova, M. N. "DEVELOPMENT OF EQUIPMENT MANAGEMENT SYSTEM WITH MONITORING OF WORKING CHARACTERISTICS OF TECHNOLOGICAL PROCESSES." In STATE AND DEVELOPMENT PROSPECTS OF AGRIBUSINESS. DSTU-PRINT, 2020. http://dx.doi.org/10.23947/interagro.2020.1.389-392.
Zhelyazov, Todor, and Radan Ivanov. "Modeling of the behaviour of concrete elements containing a self- healing agent." In IABSE Congress, Ghent 2021: Structural Engineering for Future Societal Needs. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2021. http://dx.doi.org/10.2749/ghent.2021.0079.
Zhelyazov, Todor, and Radan Ivanov. "Modeling of the behaviour of concrete elements containing a self- healing agent." In IABSE Congress, Ghent 2021: Structural Engineering for Future Societal Needs. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2021. http://dx.doi.org/10.2749/ghent.2021.0079.
Reports on the topic "General-purpose agent":
van der Mensbrugghe, Dominique. The Standard GTAP Model in GAMS, Version 7.1. GTAP Working Paper, April 2023. http://dx.doi.org/10.21642/gtap.wp92.
Johnson, Corey, Colton James, Sarah Traughber, and Charles Walker. Postoperative Nausea and Vomiting Implications in Neostigmine versus Sugammadex. University of Tennessee Health Science Center, July 2021. http://dx.doi.org/10.21007/con.dnp.2021.0005.
Belkin, Shimshon, Sylvia Daunert, and Mona Wells. Whole-Cell Biosensor Panel for Agricultural Endocrine Disruptors. United States Department of Agriculture, December 2010. http://dx.doi.org/10.32747/2010.7696542.bard.
Ocampo-Gaviria, José Antonio, Roberto Steiner Sampedro, Mauricio Villamizar Villegas, Bibiana Taboada Arango, Jaime Jaramillo Vallejo, Olga Lucia Acosta-Navarro, and Leonardo Villar Gómez. Report of the Board of Directors to the Congress of Colombia - March 2023. Banco de la República de Colombia, June 2023. http://dx.doi.org/10.32468/inf-jun-dir-con-rep-eng.03-2023.