Journal articles: 'Multi-actor systems'

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Pruyt, Erik. "Multi-actor systems and ethics." International Transactions in Operational Research 17, no. 4 (May 25, 2010): 507–20. http://dx.doi.org/10.1111/j.1475-3995.2009.00729.x.

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Grogan, Paul T., Koki Ho, Alessandro Golkar, and Olivier L. de Weck. "Multi-Actor Value Modeling for Federated Systems." IEEE Systems Journal 12, no. 2 (June 2018): 1193–202. http://dx.doi.org/10.1109/jsyst.2016.2626981.

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Heredia, Paulo C., and Shaoshuai Mou. "Distributed Multi-Agent Reinforcement Learning by Actor-Critic Method." IFAC-PapersOnLine 52, no. 20 (2019): 363–68. http://dx.doi.org/10.1016/j.ifacol.2019.12.182.

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Torres, Ana I., and George Stephanopoulos. "Design of multi-actor distributed processing systems: A game-theoretical approach." AIChE Journal 62, no. 9 (July 15, 2016): 3369–91. http://dx.doi.org/10.1002/aic.15395.

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Lempinen, Heikki, and Risto Rajala. "Exploring Multi-Actor Value Creation in IT Service Processes." Journal of Information Technology 29, no. 2 (June 2014): 170–85. http://dx.doi.org/10.1057/jit.2014.1.

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Organizational information technology (IT) needs are served through increasingly complex configurations of people, technologies, organizations, and shared information. Ideally, an organizational IT service is valuable for both the providers and users of systems and solutions. However, mutually beneficial outcomes may be difficult to achieve within the configurations through which IT services are delivered. We suggest that analyzing stakeholder interplay in IT service processes helps us to understand how information systems (IS) organizations can be leveraged to co-create business value. Through a qualitative empirical inquiry, we explore IT service realization in two case organizations. Through our analysis we find that value creation builds on orchestrated social action among the different stakeholder groups involved. Joint value creation in IT service processes hence calls for specific network leadership and resource integration capabilities from the IS organization. The paper enriches the current understanding of business value creation in IT services by infusing the service logic with traditional IT management perspectives. The findings highlight that the extent to which the IS organization can learn to facilitate the interaction between the essential actors in an ‘IT service system’ and leverage user-perceived value throughout the service process will ultimately determine its success or failure.

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Zhang, Haifeng, Weizhe Chen, Zeren Huang, Minne Li, Yaodong Yang, Weinan Zhang, and Jun Wang. "Bi-Level Actor-Critic for Multi-Agent Coordination." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (April 3, 2020): 7325–32. http://dx.doi.org/10.1609/aaai.v34i05.6226.

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Coordination is one of the essential problems in multi-agent systems. Typically multi-agent reinforcement learning (MARL) methods treat agents equally and the goal is to solve the Markov game to an arbitrary Nash equilibrium (NE) when multiple equilibra exist, thus lacking a solution for NE selection. In this paper, we treat agents unequally and consider Stackelberg equilibrium as a potentially better convergence point than Nash equilibrium in terms of Pareto superiority, especially in cooperative environments. Under Markov games, we formally define the bi-level reinforcement learning problem in finding Stackelberg equilibrium. We propose a novel bi-level actor-critic learning method that allows agents to have different knowledge base (thus intelligent), while their actions still can be executed simultaneously and distributedly. The convergence proof is given, while the resulting learning algorithm is tested against the state of the arts. We found that the proposed bi-level actor-critic algorithm successfully converged to the Stackelberg equilibria in matrix games and find a asymmetric solution in a highway merge environment.

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Leon, Florin. "ActressMAS, a .NET Multi-Agent Framework Inspired by the Actor Model." Mathematics 10, no. 3 (January 26, 2022): 382. http://dx.doi.org/10.3390/math10030382.

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Multi-agent systems show great promise in the actual state of increasing interconnectedness and autonomy of computer systems. This paper presents a .NET multi-agent framework for experimenting with agents and building multi-agent simulations. Its main advantages are conceptual simplicity and ease of use, which make it suitable for teaching agent-based notions. Several algorithms, protocols and simulations using this framework are also presented.

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Falayi, Menelisi, James Gambiza, and Michael Schoon. "Unpacking Changing Multi-Actor and Multi-Level Actor Ties in Transformative Spaces: Insights from a Degraded Landscape, Machubeni, South Africa." Land 9, no. 7 (July 13, 2020): 227. http://dx.doi.org/10.3390/land9070227.

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The loss of ecosystem services through land degradation continues to be a significant concern for policymakers and land users around the world. Facilitating collective action among various actors is regarded as imperative in halting land degradation. Despite extensive research on collective action, there have been few studies that continuously map social ties and detect network evolution as a way of enabling longitudinal analysis of transformative spaces. This paper seeks to examine the changing dynamics of multi-actor and multi-level actor ties over a period of two years in Machubeni, South Africa. To do this, we used social network analysis to detect continuities and/or discontinuities of multi-actor and multi-level actor ties over time. Overall, edge density, clustering coefficient, and reciprocity scores steadily increased over the two years despite a decline in the number of active organisations within the network. Our results demonstrate that the proportion of strong ties gradually increased over time across three governance networks. However, multi-level linkages between the local municipality and the local organisations remained weak due to a lack of trust and collaborative fatigue. While the transformative space has succeeded in enhancing collaboration and knowledge sharing between local organisations and researchers, further long-term engagement with government agencies might be necessary for promoting institutional transformations and policy outcomes, and building network resilience in complex polycentric governance systems.

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HEGRE, HÅVARD. "Trade Decreases Conflict More in Multi-actor Systems: A Comment on Dorussen." Journal of Peace Research 39, no. 1 (January 2002): 109–14. http://dx.doi.org/10.1177/0022343302039001006.

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Scheller, Fabian, Balthasar Burgenmeister, Hendrik Kondziella, Stefan Kühne, David G. Reichelt, and Thomas Bruckner. "Towards integrated multi-modal municipal energy systems: An actor-oriented optimization approach." Applied Energy 228 (October 2018): 2009–23. http://dx.doi.org/10.1016/j.apenergy.2018.07.027.

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Yue, Longfei, Rennong Yang, Jialiang Zuo, Mengda Yan, Xiaoru Zhao, and Maolong Lv. "Factored Multi-Agent Soft Actor-Critic for Cooperative Multi-Target Tracking of UAV Swarms." Drones 7, no. 3 (February 22, 2023): 150. http://dx.doi.org/10.3390/drones7030150.

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In recent years, significant progress has been made in the multi-target tracking (MTT) of unmanned aerial vehicle (UAV) swarms. Most existing MTT approaches rely on the ideal assumption of a pre-set target trajectory. However, in practice, the trajectory of a moving target cannot be known by the UAV in advance, which poses a great challenge for realizing real-time tracking. Meanwhile, state-of-the-art multi-agent value-based methods have achieved significant progress for cooperative tasks. In contrast, multi-agent actor-critic (MAAC) methods face high variance and credit assignment issues. To address the aforementioned issues, this paper proposes a learning-based factored multi-agent soft actor-critic (FMASAC) scheme under the maximum entropy framework, where the UAV swarm is able to learn cooperative MTT in an unknown environment. This method introduces the idea of value decomposition into the MAAC setting to reduce the variance in policy updates and learn efficient credit assignment. Moreover, to further increase the detection tracking coverage of a UAV swarm, a spatial entropy reward (SER), inspired by the spatial entropy concept, is proposed in this scheme. Experiments demonstrated that the FMASAC can significantly improve the cooperative MTT performance of a UAV swarm, and it outperforms existing baselines in terms of the mean reward and tracking success rates. Additionally, the proposed scheme scales more successfully as the number of UAVs and targets increases.

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Bendahan, Samuel, Giovanni Camponovo, and Yves Pigneur. "Multi-Issue Actor Analysis: Tools and Models for Assessing Technology Environments." Journal of Decision Systems 13, no. 2 (January 2004): 223–53. http://dx.doi.org/10.3166/jds.13.223-253.

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MANTOVANI, GIUSEPPE, and MIRCO BOLZONI. "Analysing and evaluating multi-actor multi-goal systems in use: social contexts and participation in three Vocational Guidance Systems (VGS)." Behaviour & Information Technology 13, no. 3 (May 1994): 201–15. http://dx.doi.org/10.1080/01449299408914600.

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Dey, Shawon, and Hao Xu. "Intelligent Distributed Swarm Control for Large-Scale Multi-UAV Systems: A Hierarchical Learning Approach." Electronics 12, no. 1 (December 26, 2022): 89. http://dx.doi.org/10.3390/electronics12010089.

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In this paper, a distributed swarm control problem is studied for large-scale multi-agent systems (LS-MASs). Different than classical multi-agent systems, an LS-MAS brings new challenges to control design due to its large number of agents. It might be more difficult for developing the appropriate control to achieve complicated missions such as collective swarming. To address these challenges, a novel mixed game theory is developed with a hierarchical learning algorithm. In the mixed game, the LS-MAS is represented as a multi-group, large-scale leader–follower system. Then, a cooperative game is used to formulate the distributed swarm control for multi-group leaders, and a Stackelberg game is utilized to couple the leaders and their large-scale followers effectively. Using the interaction between leaders and followers, the mean field game is used to continue the collective swarm behavior from leaders to followers smoothly without raising the computational complexity or communication traffic. Moreover, a hierarchical learning algorithm is designed to learn the intelligent optimal distributed swarm control for multi-group leader–follower systems. Specifically, a multi-agent actor–critic algorithm is developed for obtaining the distributed optimal swarm control for multi-group leaders first. Furthermore, an actor–critic–mass method is designed to find the decentralized swarm control for large-scale followers. Eventually, a series of numerical simulations and a Lyapunov stability proof of the closed-loop system are conducted to demonstrate the performance of the developed scheme.

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Amrina, Uly, Akhmad Hidayatno, and Teuku Yuri M. Zagloel. "Mapping challenges in developing sustainable small and medium industries: Integrating Lean and green principles." Journal of Industrial Engineering and Management 14, no. 2 (March 9, 2021): 311. http://dx.doi.org/10.3926/jiem.3401.

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Purpose: This study explores the complexity of developing a sustainable small and medium industry (SMI) through a conceptual model that integrates lean and green manufacturing principles.Design/methodology/approach: This model includes a systems diagram that illustrates the structure of the interconnected variable and the interrelationships between goals, inputs, processes, and outputs required to achieve a system’s goals by using both lean and green principles. The diagram uses causal loop diagram logic from systems thinking based on the literature review, multi-actor analysis, observations, and focus group discussions.Findings: Combining the efficiency benefits from lean principles and better environmental effectiveness from green principles would help to achieve sustainability. A conceptual structural map could support the integration processes by illustrating the variables, multi-actors, and multi-indicators required to achieve sustainability.Research limitations/implications: The conceptual model highlights the necessary linkage between lean and green practices that would help SMI researchers and decision-makers to navigate their activities in achieving sustainability.Originality/value: There is currently little discussion at the SMI level from a multi-actor perspective. The systems diagram offers a comprehensive picture that is the basis for further discussion of the complexity of integrating lean and green principles.

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Suttle, Wesley, Zhuoran Yang, Kaiqing Zhang, Zhaoran Wang, Tamer Başar, and Ji Liu. "A Multi-Agent Off-Policy Actor-Critic Algorithm for Distributed Reinforcement Learning." IFAC-PapersOnLine 53, no. 2 (2020): 1549–54. http://dx.doi.org/10.1016/j.ifacol.2020.12.2021.

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Wang, Wei, and Xin Chen. "Model-free optimal containment control of multi-agent systems based on actor-critic framework." Neurocomputing 314 (November 2018): 242–50. http://dx.doi.org/10.1016/j.neucom.2018.06.011.

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Mushtaq, Anum, Irfan Ul Haq, Muhammad Azeem Sarwar, Asifullah Khan, Wajeeha Khalil, and Muhammad Abid Mughal. "Multi-Agent Reinforcement Learning for Traffic Flow Management of Autonomous Vehicles." Sensors 23, no. 5 (February 21, 2023): 2373. http://dx.doi.org/10.3390/s23052373.

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Intelligent traffic management systems have become one of the main applications of Intelligent Transportation Systems (ITS). There is a growing interest in Reinforcement Learning (RL) based control methods in ITS applications such as autonomous driving and traffic management solutions. Deep learning helps in approximating substantially complex nonlinear functions from complicated data sets and tackling complex control issues. In this paper, we propose an approach based on Multi-Agent Reinforcement Learning (MARL) and smart routing to improve the flow of autonomous vehicles on road networks. We evaluate Multi-Agent Advantage Actor-Critic (MA2C) and Independent Advantage Actor-Critical (IA2C), recently suggested Multi-Agent Reinforcement Learning techniques with smart routing for traffic signal optimization to determine its potential. We investigate the framework offered by non-Markov decision processes, enabling a more in-depth understanding of the algorithms. We conduct a critical analysis to observe the robustness and effectiveness of the method. The method’s efficacy and reliability are demonstrated by simulations using SUMO, a software modeling tool for traffic simulations. We used a road network that contains seven intersections. Our findings show that MA2C, when trained on pseudo-random vehicle flows, is a viable methodology that outperforms competing techniques.

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Van Hennik, Robert. "Becoming a posthuman systemic nomad. Part II: Systemic Nomads. An Ecosophy." Murmurations: Journal of Transformative Systemic Practice 3, no. 2 (January 31, 2021): 1–29. http://dx.doi.org/10.28963/3.2.2.

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In the second part of the text “Becoming a posthuman systemic nomad”, I suggest ways in which systemic practitioners may become systemic nomads, reintegrating cybernetics and social constructionism and taking a new-materialist perspective on life. Systemic therapists may become “post human systemic nomads”, navigating and systemically learning in complex adaptive systems, in which we are relational responsible to all human and non-human actors in the networks that we produce and that we are produced by. Inspired by the philosophy of Deleuze and Guattari I made three cartographies for us, systemic nomads, navigating complexity in multi-actor systems. Systemic practitioners (from a new-materialist perspective) can co-create better ecological worlds if we are conscious of the effects of our actions in interdependent relationships with all actors in life, when – as nomads – we display systemic sensibility or intelligence (Senge, 2006) within systems of multi-actors. Abstract (Dutch) In dit tweede deel van de tekst “Becoming a posthuman systemic nomad” beschrijf ik hoe systeemtherapeuten en consulenten “systemische nomaden” kunnen worden door in hun denken en doen inspiraties uit de cybernetica, het sociaal constructionisme en het nieuw-materialisme te integreren. Systeemtherapeuten en ‘systemisch’ consulenten, die “systemische nomaden” worden, navigeren en leren navigeren in complex adaptieve multi-actor systemen. Zij ervaren een ‘relationele verantwoordelijkheid’ naar zowel humane als niet-humane (dingen, dieren, planten) actoren in de netwerken waartoe zij betekenisvol bijdragen, waarvan zij om betekenisvol voort te bestaan afhankelijk zijn. “Systemische nomaden”, bewust van de inter-afhankelijkheid tussen alle humane en niet-humane deelnemers in het multi-actor netwerk, kunnen mogelijk bijdragen in de co-creatie van betere ecologisch afgestemde leefwerelden. Geïnspireerd door de filosofie van Deleuze en Guattari maakte ik drie cartografieën die ons in dit proces van navigeren en leren navigeren kunnen helpen.

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Hyland, John J., and Áine Macken-Walsh. "Multi-Actor Social Networks: A Social Practice Approach to Understanding Food Hubs." Sustainability 14, no. 3 (February 7, 2022): 1894. http://dx.doi.org/10.3390/su14031894.

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Food hubs are collaborative entities that strategically manage the assemblage, delivery, and promotion of food from a range of local food producers. They are essentially multi-actor institutions, involving horizontal collaboration between producers and vertical collaborations up and down the food chain, involving all actors required to bring food products from producers to consumers. Although food hubs offer many advantages to both producers and consumers, they remain a recognisably neglected research topic in Europe. Furthermore, the strategic networks of actors involved in these collaborative entities is often overlooked. Empirically, this study draws from a collection of ‘good practices’ gathered for the Short Supply Chain Knowledge and Innovation Network (SKIN) EU-funded H2020 project. Drawing on a social practice approach and network diagrams, this article explores the good practices of three food hub typologies. This study primarily investigates the context in which food hubs practice multi-actor food provision. We apply social practice as a lens to ’zoom in’ and explore the shared materials, meanings and skills that aid such systems of provision. Social network diagrams are utilised to ‘zoom out’ to examine and facilitate the detection of key actors involved in food hubs’ strategic networks. This research addresses the lack of academic attention on European food hubs by placing practice as the central unit of focus. Our approach enables better comprehension of what constitutes a short food supply chain (SFSC) when orchestrated within three main typologies of food hubs. The findings are of interest to researchers, policy makers, agricultural development intermediaries, and actors involved in systems of food provision who are interested in understanding and supporting the functioning of SFSCs.

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Anke, Jürgen, Jens Poeppelbuss, and Rainer Alt. "It Takes More than Two to Tango: Identifying Roles and Patterns in Multi-Actor Smart Service Innovation." Schmalenbach Business Review 72, no. 4 (September 15, 2020): 599–634. http://dx.doi.org/10.1007/s41464-020-00101-2.

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Abstract Smart service systems enable innovative value propositions based on smart products and data-driven value creation. Grounded in service-dominant logic as our theoretical lens, we argue that smart service innovation takes place in ecosystems of collaborating actors, as a single actor does not possess all required resources and competencies. We empirically explore smart service innovation using an interview study of 14 experts who were involved in real-world smart service systems engineering projects. As a result, we conceptualize 17 roles that describe the resources and competencies required for smart service innovation at an abstract level. Through the analysis of actor-role constellations in our sample of projects, we further identify four patterns that exhibit different strategic approaches to smart service innovation. Our results advance the theoretical understanding of smart service systems through an empirically grounded systematization of roles, which reflect the resources and competencies required for smart service innovation. With this study, we shed light on the multi-actor and inter-organizational settings of service innovation processes, which have been under-researched so far. Our insights are further helpful for practitioners, who participate in the smart service innovation and who need to analyze their strategic position in service ecosystems.

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Avkhimenia, Vadim, Matheus Gemignani, Tim Weis, and Petr Musilek. "Deep Reinforcement Learning-Based Operation of Transmission Battery Storage with Dynamic Thermal Line Rating." Energies 15, no. 23 (November 29, 2022): 9032. http://dx.doi.org/10.3390/en15239032.

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It is well known that dynamic thermal line rating has the potential to use power transmission infrastructure more effectively by allowing higher currents when lines are cooler; however, it is not commonly implemented. Some of the barriers to implementation can be mitigated using modern battery energy storage systems. This paper proposes a combination of dynamic thermal line rating and battery use through the application of deep reinforcement learning. In particular, several algorithms based on deep deterministic policy gradient and soft actor critic are examined, in both single- and multi-agent settings. The selected algorithms are used to control battery energy storage systems in a 6-bus test grid. The effects of load and transmissible power forecasting on the convergence of those algorithms are also examined. The soft actor critic algorithm performs best, followed by deep deterministic policy gradient, and their multi-agent versions in the same order. One-step forecasting of the load and ampacity does not provide any significant benefit for predicting battery action.

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Li, Xinzhou, Guifen Chen, Guowei Wu, Zhiyao Sun, and Guangjiao Chen. "Research on Multi-Agent D2D Communication Resource Allocation Algorithm Based on A2C." Electronics 12, no. 2 (January 10, 2023): 360. http://dx.doi.org/10.3390/electronics12020360.

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Device to device (D2D) communication technology is the main component of future communication, which greatly improves the utilization of spectrum resources. However, in the D2D subscriber multiplex communication network, the interference between communication links is serious and the system performance is degraded. Traditional resource allocation schemes need a lot of channel information when dealing with interference problems in the system, and have the problems of weak dynamic resource allocation capability and low system throughput. Aiming at this challenge, this paper proposes a multi-agent D2D communication resource allocation algorithm based on Advantage Actor Critic (A2C). First, a multi-D2D cellular communication system model based on A2C Critic is established, then the parameters of the actor network and the critic network in the system are updated, and finally the resource allocation scheme of D2D users is dynamically and adaptively output. The simulation results show that compared with DQN (deep Q-network) and MAAC (multi-agent actor–critic), the average throughput of the system is improved by 26% and 12.5%, respectively.

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Tliche, Youssef, Atour Taghipour, Jomana Mahfod-Leroux, and Mohammadali Vosooghidizaji. "Collaborative Bullwhip Effect-Oriented Bi-Objective Optimization for Inference-Based Weighted Moving Average Forecasting in Decentralized Supply Chain." International Journal of Information Systems and Supply Chain Management 16, no. 1 (January 13, 2023): 1–37. http://dx.doi.org/10.4018/ijisscm.316168.

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Downstream demand inference (DDI) emerged in the supply chain theory, allowing an upstream actor to infer the demand occurring at his formal downstream actor without need of information sharing. Literature showed that simultaneously minimizing the average inventory level and the bullwhip effect isn't possible. In this paper, the authors show that demand inference is not only possible between direct supply chain links, but also at any downstream level. The authors propose a bi-objective approach to reduce both performance indicators by adopting the genetic algorithm. Simulation results show that bullwhip effect can be reduced highly if specific configurations are selected from the Pareto frontier. Numerical results show that demand's time-series structure, lead-times, holding and shortage costs, don't affect the behaviour of the bullwhip effect indicator. Moreover, the sensitivity analysis show that the optimization approach is robust when faced to varied initializations. Finally, the authors conclude the paper with managerial implications in multi-level supply chains.

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Salvia, Rosanna, and Giovanni Quaranta. "Multi-Actor Platform as a tool to enhance networking of sustainable socio-ecological food systems." ECONOMIA AGRO-ALIMENTARE, no. 2 (September 2019): 405–27. http://dx.doi.org/10.3280/ecag2019-002012.

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Kauffeld-Monz, Martina, and Michael Fritsch. "Who Are the Knowledge Brokers in Regional Systems of Innovation? A Multi-Actor Network Analysis." Regional Studies 47, no. 5 (May 2013): 669–85. http://dx.doi.org/10.1080/00343401003713365.

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Szemenyei, Márton, and Patrik Reizinger. "Handling Realistic Noise in Multi-Agent Systems with Self-Supervised Learning and Curiosity." Journal of Artificial Intelligence and Soft Computing Research 12, no. 2 (April 1, 2021): 135–48. http://dx.doi.org/10.2478/jaiscr-2022-0009.

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Abstract 1Most reinforcement learning benchmarks – especially in multi-agent tasks – do not go beyond observations with simple noise; nonetheless, real scenarios induce more elaborate vision pipeline failures: false sightings, misclassifications or occlusion. In this work, we propose a lightweight, 2D environment for robot soccer and autonomous driving that can emulate the above discrepancies. Besides establishing a benchmark for accessible multi-agent reinforcement learning research, our work addresses the challenges the simulator imposes. For handling realistic noise, we use self-supervised learning to enhance scene reconstruction and extend curiosity-driven learning to model longer horizons. Our extensive experiments show that the proposed methods achieve state-of-the-art performance, compared against actor-critic methods, ICM, and PPO.

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Knippenberg, S. C. M., L. F. P. Etman, T. Wilschut, and J. A. van de Mortel-Fronczak. "Specifying Process Activities for Multi-Domain Matrix Analysis Using a Structured Textual Format." Proceedings of the Design Society: International Conference on Engineering Design 1, no. 1 (July 2019): 1613–22. http://dx.doi.org/10.1017/dsi.2019.167.

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AbstractThis paper proposes a method to automatically generate a multi-domain matrix (MDM) from textual activity specifications. The format for specifying these activities is based on a structured grammar derived from natural language and consists of two types of activities: goal activities and transformation activities. A goal activity describes the purpose of an action performed by an actor for the benefit of another actor in the system. A transformation activity describes an activity from the viewpoint of a single actor, who receives, generates, and outputs information or artifacts. If one describes activities using these two types of activity specifications, dependencies can be automatically derived between actors, activities, and parameters of the system and visualized in an MDM. Thus the generated MDM presents an organization DSM (actors), a process DSM (activities), and a parameter DSM (flows of information or objects), as well as the mapping matrices coupling the different domains. An illustrative house construction example demonstrates the effectiveness of the proposed activity specification format. The method may provide an outcome in understanding and managing complex systems.

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Sofi, Francesco, Monica Dinu, Giuditta Pagliai, Leonardo Cei, Giovanna Sacchi, Stefano Benedettelli, Gianluca Stefani, et al. "Health and Nutrition Studies Related to Cereal Biodiversity: A Participatory Multi-Actor Literature Review Approach." Nutrients 10, no. 9 (September 1, 2018): 1207. http://dx.doi.org/10.3390/nu10091207.

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Recently, a large and growing body of literature has investigated the health potential of different wheat species. In particular, a considerable number of studies dealing with nutritional aspects has grown up around the theme of the recovery of ancient wheat varieties (species that have remained unchanged over the last hundred years). According to several studies, indeed, ancient varieties present a healthier nutritional profile than modern ones. In the framework of the European project “CERERE, CEreal REnaissance in Rural Europe: embedding diversity in organic and low-input food systems”, this paper aimed to review recent research on the issue of health and nutritional cereal systems by adopting an innovative and participatory multi-actor approach which involved practitioners along with researchers. The participatory approach is the main innovation and peculiarity of this literature review. Nevertheless, the review highlights the many positive effects derived from eating whole and ancient grains such as a significant reduction in the risk of chronic diseases such as cancer, cardiovascular disease, and also a more favorable long-term weight management and increase in satiety. This review may be considered as a fruitful starting point that integrates research results to foster current and future healthier and sustainable practices in cereal systems.

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Cockburn, Jessica, Eureta Rosenberg, Athina Copteros, Susanna Francina (Ancia) Cornelius, Notiswa Libala, Liz Metcalfe, and Benjamin van der Waal. "A Relational Approach to Landscape Stewardship: Towards a New Perspective for Multi-Actor Collaboration." Land 9, no. 7 (July 10, 2020): 224. http://dx.doi.org/10.3390/land9070224.

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Landscape stewardship is increasingly understood within the framing of complex social-ecological systems. To consider the implications of this, we focus on one of the key characteristics of complex social-ecological systems: they are relationally constituted, meaning that system characteristics emerge out of dynamic relations between system components. We focus on multi-actor collaboration as a key form of relationality in landscapes, seeking a more textured understanding of the social relations between landscape actors. We draw on a set of ‘gardening tools’ to analyse the boundary-crossing work of multi-actor collaboration. These tools comprise three key concepts: relational expertise, common knowledge, and relational agency. We apply the tools to two cases of landscape stewardship in South Africa: the Langkloof Region and the Tsitsa River catchment. These landscapes are characterised by economically, socio-culturally, and politically diverse groups of actors. Our analysis reveals that history and context strongly influence relational processes, that boundary-crossing work is indeed difficult, and that doing boundary-crossing work in smaller pockets within a landscape is helpful. The tools also helped to identify three key social-relational practices which lend a new perspective on boundary-crossing work: 1. belonging while differing, 2. growing together by interacting regularly and building common knowledge, and 3. learning and adapting together with humility and empathy.

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Sacchi, Giovanna, Leonardo Cei, Gianluca Stefani, Ginevra Lombardi, Benedetto Rocchi, Giovanni Belletti, Susanne Padel, et al. "A Multi-Actor Literature Review on Alternative and Sustainable Food Systems for the Promotion of Cereal Biodiversity." Agriculture 8, no. 11 (November 2, 2018): 173. http://dx.doi.org/10.3390/agriculture8110173.

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Organic and low-input food systems are emerging worldwide in answer to the sustainability crisis of the conventional agri-food sector. “Alternative” systems are based on local, decentralized approaches to production and processing, regarding quality and health, and short supply-chains for products with strong local identities. Diversity is deeply embedded in these food systems, from the agrobiodiversity grown in farmers’ fields, which improves resilience and adaptation, to diverse approaches, contexts and actors in food manufacturing and marketing. Diversity thus becomes a cross-sectoral issue which acknowledges consumers’ demand for healthy products. In the framework of the European project “CERERE, CEreal REnaissance in Rural Europe: embedding diversity in organic and low-input food systems”, the paper aims at reviewing recent research on alternative and sustainable food systems by adopting an innovative and participatory multi-actor approach; this has involved ten practitioners and twenty-two researchers from across Europe and a variety of technical backgrounds in the paper and analysis stages. The participatory approach is the main innovation and distinctive feature of this literature review. Partners selected indeed what they perceived as most relevant in order to facilitate a transition towards more sustainable and diversity based cereal systems and food chains. This includes issues related to alternative food networks, formal and informal institutional settings, grass root initiatives, consumer involvement and, finally, knowledge exchange and sustainability. The review provides an overview of recent research that is relevant to CERERE partners as well as to anyone interested in alternative and sustainable food systems. The main objective of this paper was indeed to present a narrative of studies, which can form the foundation for future applied research to promote alternative methods of cereal production in Europe.

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Kovalevsky, Dmitry V., Richard Hewitt, Cheryl de Boer, and Klaus Hasselmann. "A Dynamic Systems Approach to the Representation of Policy Implementation Processes in a Multi-Actor World." Interdisciplinary journal of Discontinuity, Complexity, and Nonlinearity 6, no. 3 (September 2017): 219–45. http://dx.doi.org/10.5890/dnc.2017.09.001.

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Cuevas, Á., M. Urueña, R. Cuevas, and R. Romeral. "Modelling data-aggregation in multi-replication data centric storage systems for wireless sensor and actor networks." IET Communications 5, no. 12 (August 12, 2011): 1669–81. http://dx.doi.org/10.1049/iet-com.2010.0574.

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Xu, Haotian, Qi Fang, Cong Hu, Yue Hu, and Quanjun Yin. "MIRA: Model-Based Imagined Rollouts Augmentation for Non-Stationarity in Multi-Agent Systems." Mathematics 10, no. 17 (August 25, 2022): 3059. http://dx.doi.org/10.3390/math10173059.

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One of the challenges in multi-agent systems comes from the environmental non-stationarity that policies of all agents are evolving individually over time. Many existing multi-agent reinforcement learning (MARL) methods have been proposed to address this problem. However, these methods rely on a large amount of training data and some of them require agents to intensely communicate, which is often impractical in real-world applications. To better tackle the non-stationarity problem, this article combines model-based reinforcement learning (MBRL) and meta-learning and proposes a method called Model-based Imagined Rollouts Augmentation (MIRA). Based on an environment dynamics model, distributed agents can independently perform multi-agent rollouts with opponent models during exploitation and learn to infer the environmental non-stationarity as a latent variable using the rollouts. Based on the world model and latent-variable inference module, we perform multi-agent soft actor-critic implementation for centralized training and decentralized decision making. Empirical results on the Multi-agent Particle Environment (MPE) have proved that the algorithm has a very considerable improvement in sample efficiency as well as better convergent rewards than state-of-the-art MARL methods, including COMA, MAAC, MADDPG, and VDN.

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Jungblut, Jens, and Deanna Rexe. "Higher education policy in Canada and Germany: Assessing multi-level and multi-actor coordination bodies for policy-making in federal systems." Policy and Society 36, no. 1 (January 2, 2017): 49–66. http://dx.doi.org/10.1080/14494035.2017.1278864.

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Castro, Antonio J., María D. López-Rodríguez, Cynthia Giagnocavo, Miguel Gimenez, Leticia Céspedes, Abel La Calle, Marisa Gallardo, et al. "Six Collective Challenges for Sustainability of Almería Greenhouse Horticulture." International Journal of Environmental Research and Public Health 16, no. 21 (October 24, 2019): 4097. http://dx.doi.org/10.3390/ijerph16214097.

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Globally, current food consumption and trade are placing unprecedented demand on agricultural systems and increasing pressure on natural resources, requiring tradeoffs between food security and environmental impacts especially given the tension between market-driven agriculture and agro-ecological goals. In order to illustrate the wicked social, economic and environmental challenges and processes to find transformative solutions, we focus on the largest concentration of greenhouses in the world located in the semi-arid coastal plain of South-east Spain. Almería family farming, predominantly cooperative, greenhouse intensive production, commenced after the 1960s and has resulted in very significant social and economic benefits for the region, while also having important negative environmental and biodiversity impacts, as well as creating new social challenges. The system currently finds itself in a crisis of diminishing economic benefits and increasing environmental and social dilemmas. Here, we present the outcomes of multi-actor, transdisciplinary research to review and provide collective insights for solutions-oriented research on the sustainability of Almeria’s agricultural sector. The multi-actor, transdisciplinary process implemented collectively, and supported by scientific literature, identified six fundamental challenges to transitioning to an agricultural model that aims to ameliorate risks and avoid a systemic collapse, whilst balancing a concern for profitability with sustainability: (1) Governance based on a culture of shared responsibility for sustainability, (2) Sustainable and efficient use of water, (3) Biodiversity conservation, (4) Implementing a circular economy plan, (5) Technology and knowledge transfer, and (6) Image and identity. We conclude that the multi-actor transdisciplinary approach successfully facilitated the creation of a culture of shared responsibility among public, private, academic, and civil society actors. Notwithstanding plural values, challenges and solutions identified by consensus point to a nascent acknowledgement of the strategic necessity to locate agricultural economic activity within social and environmental spheres.This paper demonstrates the need to establish transdisciplinary multi-actor work-schemes to continue collaboration and research for the transition to an agro-ecological model as a means to remain competitive and to create value.

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Wang, Qiuchen, Jannicke Baalsrud Hauge, and Sebastiaan Meijer. "Adopting an Actor Analysis Framework to a Complex Technology Innovation Project: A Case Study of an Electric Road System." Sustainability 12, no. 1 (December 31, 2019): 313. http://dx.doi.org/10.3390/su12010313.

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An electric road system (ERS) is a transportation solution that provides electricity for fully electric vehicles while in motion. This solution might contribute to sustainable transportation by overcoming range anxiety problems that fully electric vehicles, especially heavy vehicles, have encountered due to battery technology limitations. However, large-scale ERS implementations are challenging, both technically and socially. An ERS is not only an engineering project, but also a complex technology innovation system composed of multiple subsystems and stakeholders, which requires an interdisciplinary means of aligning relations, problems, and solutions. In the policy analysis domain, researchers have developed actor analysis methods to support policy making processes. Actor analysis methods can provide an analytical reflection in solving complex multi-actor policy making challenges that ERSs are also facing. To uncover the complexity of multiple subsystems and stakeholders involved in an ERS, this paper applied a method to align system characteristics with the stakeholders’ perceptions to understand multi-stakeholder contexts in complex technology innovation projects. Desk research was first conducted to summarise ERS characteristics. Then, the dynamic actor network analysis method framework was adopted to establish an action, factor, goal (AFG) list, which was revised by independent researchers. Next, the AFG list was used to collect the perceptions of the ERS stakeholders, expressed as AFG selections and causal links through stakeholder interviews. The resulting AFG list was iterated through two rounds of interviews and then validated in a Swedish ERS case workshop. The results from this methodology showed that the actor analysis method can not only be applied to policy analysis domains, but can also be applied to technology innovation complex systems, using the electric road system as a case study, to help uncover the ERS complexity from the concerns of stakeholders and to secure a pathway towards sustainable technology implementation.

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Agusdinata, D. Buyung, and Daniel A. Delaurentis. "Addressing equity issue in multi-actor policymaking via a system-of-systems approach: Aviation emissions reduction case study." Journal of Systems Science and Systems Engineering 20, no. 1 (February 25, 2011): 1–24. http://dx.doi.org/10.1007/s11518-011-5156-z.

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Bohle, Martin, Cornelia Nauen, and Eduardo Marone. "Ethics to Intersect Civic Participation and Formal Guidance." Sustainability 11, no. 3 (February 1, 2019): 773. http://dx.doi.org/10.3390/su11030773.

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Sound governance arrangement in socio-ecological systems (human niche) combines different means of sense-making. The sustainability of human niche-building depends on the governability of the social-ecological systems (SES) forming the niche. Experiences from small-scale marine fisheries and seabed mining illustrate how ethical frameworks, civic participation and formalised guidance combine in the context of a “blue economy”. Three lines of inquiries contextualise these experiences driving research questions, such as “what is the function of ethics for governability?” First, complex-adaptive SES are featured to emphasise the sense-making feedback loop in SES. Actors are part of this feedback loop and can use different means of sense-making to guide their actions. Second, the “Voluntary Guidelines for Sustainable Small-Scale Fisheries” and geoethical thinking are featured to highlight the relevance of actor-centric concepts. Third, Kohlberg’s model of “stages of moral adequacy” and the United Nations Convention on the Law of the Sea (UNCLOS) are used to show how to strengthen actor-centric virtue-ethics. Combining these lines of inquiry leads to the conclusion that ethical frameworks, civic participation and formalised guidance, when put in a mutual context, support governability and multi-actor/level policy-making. Further research could explore how creativity can strengthen civic participation, a feature only sketched here.

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van der Lei, T. E., and W. A. H. Thissen. "Quantitative problem structuring methods for multi-actor problems: an analysis of reported applications." Journal of the Operational Research Society 60, no. 9 (September 2009): 1198–206. http://dx.doi.org/10.1057/palgrave.jors.2008.93.

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Lixin, MA, LIU Chen, and LIU Lei. "Optimal Leader-Following Consensus Control of Fractional-Order Multi-Agent Systems Based on the Actor-Critic Algorithm." 应用数学和力学 43, no. 1 (2022): 104–14. http://dx.doi.org/10.21656/1000-0887.420124.

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Bekius, Femke, Sebastiaan Meijer, and Hugo Thomassen. "A Real Case Application of Game Theoretical Concepts in a Complex Decision-Making Process: Case Study ERTMS." Group Decision and Negotiation 31, no. 1 (October 18, 2021): 153–85. http://dx.doi.org/10.1007/s10726-021-09762-x.

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AbstractEngineering systems are complex, amongst others due to the interdependencies between actor and technical aspects. This complexity has consequences for the way of designing such systems and, in particular, for the decision-making process. Recognizing the impossibility of having an optimal system design in such complex systems, this article explores how a game theoretical characterization of a decision-making process assists in the organization and design of the process itself. In contrast to a game theoretical analysis, which results in optimal outcomes, the characterization is fed back to the designers of the decision-making process during the course of the process. The study analyses how the game concept characterization was used, i.e., which strategies were defined during the game theory interventions, and what the consequences of these strategies were for the design of the decision-making process. The design of a new safety system ERTMS for the Dutch railway sector is the context in which the study was performed. The contribution is a successful approach to complex decision-making in multi-actor systems by identification of multiple game concepts over time, with periodic feedback into the designing system, and not the actual decision-making itself. In short, it supported adapting to an actor focus on the process, it affected the role and responsibilities of the program management, it contributed to (de)coupling of issues, and it influenced the capability of creating awareness amongst actors of the urgency of the decision window. The paper ends with reflections on the experience of intervening in a decision-making process with game theoretical concepts.

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Guerrero-Ocampo, Susana B., José M. Díaz-Puente, and Juan Felipe Nuñez Espinoza. "Multi-Actor Partnerships for Agricultural Interactive Innovation: Findings from 17 Case Studies in Europe." Land 11, no. 10 (October 20, 2022): 1847. http://dx.doi.org/10.3390/land11101847.

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Innovation is widely regarded as a key factor for the economic development and competitiveness of companies and countries. It is, therefore, widely considered a policy instrument in various sectors, such as agriculture. In this sector, agricultural innovation is seen as a systemic and interactive phenomenon, which is the result of interactions between innovators and knowledge-generating organisations, as well as social and economic aspects of the context. This paper studies the social structures of multi-actor partnerships involved in interactive innovation processes in agricultural innovation systems, analysing the type of actors involved and the roles they play in the innovation process. For this purpose, 17 case studies were analysed in the framework of the Liaison project, an H2020 project, using social network analysis (SNA) and descriptive statistics. The results show that the studied multi-actor partnerships have been mostly funded by outside sources of funding, highlighting European funds. The innovation networks have a heterogeneous composition, but when we analyse the frequency of interactions there is a tendency to establish greater interaction between organisations that are of the same type. In the “core” of innovation networks, research entities and farmers are central actors with the main role of technician expert and case study field workers, respectively.

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Ren, Jingzheng, Xusheng Ren, Hanwei Liang, Liang Dong, Long Zhang, Xiao Luo, Yingkui Yang, and Zhiqiu Gao. "Multi-actor multi-criteria sustainability assessment framework for energy and industrial systems in life cycle perspective under uncertainties. Part 1: weighting method." International Journal of Life Cycle Assessment 22, no. 9 (December 21, 2016): 1397–405. http://dx.doi.org/10.1007/s11367-016-1251-1.

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Holthusen, A,, O. Riemer, E. Brinksmeier, F. Thiemicke, C. Falldorf, and R. Bergmann. "FTS-Diamantdrehen strukturierter Oberflächen*/FTS diamond turning of structured surfaces." wt Werkstattstechnik online 108, no. 11-12 (2018): 784–89. http://dx.doi.org/10.37544/1436-4980-2018-11-12-44.

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Für die Fertigung hochfunktioneller optischer Systeme eignet sich vor allem das Diamantdrehen in Kombination mit einem hochfrequenten Piezo-Versteller. Die spezifischen Herausforderungen der Herstellung komplexer Reliefphasenhologramme für die Bilderzeugung auf mehreren Rekonstruktionsebenen sollen beschrieben werden. Die Erzeugung unterschiedlicher Strukturwinkel auf dem Werkstück durch die Rotation der extrem schmalen, rechteckigen Diamantwerkzeuge ist ein Schwerpunkt der Veröffentlichung.   The machining of highly functional optical systems is particularly achieved with diamond turning in combination with a high frequency piezo actor. In the paper, the machining process for a complex multi-level holographic structure is described. Especially the challenges of the varying structure angle, generated with the rotation of the rectangular shaped diamond tools, will be addressed.

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Yang, Shantian, Bo Yang, Hau-San Wong, and Zhongfeng Kang. "Cooperative traffic signal control using Multi-step return and Off-policy Asynchronous Advantage Actor-Critic Graph algorithm." Knowledge-Based Systems 183 (November 2019): 104855. http://dx.doi.org/10.1016/j.knosys.2019.07.026.

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Iocola, Ileana, Frederique Angevin, Christian Bockstaller, Rui Catarino, Michael Curran, Antoine Messéan, Christian Schader, et al. "An Actor-Oriented Multi-Criteria Assessment Framework to Support a Transition towards Sustainable Agricultural Systems Based on Crop Diversification." Sustainability 12, no. 13 (July 6, 2020): 5434. http://dx.doi.org/10.3390/su12135434.

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Crop diversification represents a key lever to support the development of sustainable agri-food systems. Knowledge on trade-offs and carry over effects from different crop diversification strategies is essential to inform agricultural stakeholders of potential costs and benefits. This knowledge is limited by existing data and performance measures predominantly focused on single crops, rather than complete rotations. Moreover, sustainability performance indicators are often used for assessment purposes, rather than supporting stakeholder learning and actions. A new set of 32 indicators was developed to address these needs, and used to evaluate the environmental, economic and social sustainability of the diversified agricultural systems highlighted in the case studies, which are often characterized by data availability constraints. This approach was tested in France, Germany and Italy to determine a critical ex-post diagnosis of the existing systems, and for the assessment of ex-ante innovative scenarios. The results will be used to support these case studies in the identification and design of more sustainable agricultural systems. Although the framework is based on feasible and proxy indicators, the assessment outcomes have allowed local actors to reflect on the effects generated by the implemented crop diversification strategies. Key issues include trade-offs occurring between optimizing economic and environmental performance.

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Wen, Guoxing, C. L. Philip Chen, Jun Feng, and Ning Zhou. "Optimized Multi-Agent Formation Control Based on an Identifier–Actor–Critic Reinforcement Learning Algorithm." IEEE Transactions on Fuzzy Systems 26, no. 5 (October 2018): 2719–31. http://dx.doi.org/10.1109/tfuzz.2017.2787561.

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Ren, Jingzheng, Xusheng Ren, Hanwei Liang, Liang Dong, Long Zhang, Xiao Luo, Yingkui Yang, and Zhiqiu Gao. "Multi-actor multi-criteria sustainability assessment framework for energy and industrial systems in life cycle perspective under uncertainties. Part 2: improved extension theory." International Journal of Life Cycle Assessment 22, no. 9 (December 21, 2016): 1406–17. http://dx.doi.org/10.1007/s11367-016-1252-0.

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Olszewski, Robert, Piotr Pałka, Agnieszka Turek, Bogna Kietlińska, Tadeusz Płatkowski, and Marek Borkowski. "Spatiotemporal Modeling of the Smart City Residents’ Activity with Multi-Agent Systems." Applied Sciences 9, no. 10 (May 19, 2019): 2059. http://dx.doi.org/10.3390/app9102059.

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The article proposes the concept of modeling that uses multi-agent systems of mutual interactions between city residents as well as interactions between residents and spatial objects. Adopting this perspective means treating residents, as well as buildings or other spatial objects, as distinct agents that exchange multifaceted packages of information in a dynamic and non-linear way. The exchanged information may be reinforced or diminished during the process, which may result in changing the social activity of the residents. Utilizing Latour’s actor–network theory, the authors developed a model for studying the relationship between demographic and social factors, and the diversified spatial arrangement and the structure of a city. This concept was used to model the level of residents’ trust spatiotemporally and, indirectly, to study the level of social (geo)participation in a smart city. The devised system, whose test implementation as an agent-based system was done in the GAMA: agent-based, spatially explicit, modeling and simulation platform, was tested on both model and real data. The results obtained for the model city and the capital of Poland, Warsaw, indicate the significant and interdisciplinary analytical and scientific potential of the authorial methodology in the domain of geospatial science, geospatial data models with multi-agent systems, spatial planning, and applied social sciences.

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Journal articles on the topic 'Multi-actor systems'

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