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A Survey of Agent Platforms

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Abstract

From computer games to human societies, many natural and artificial phenomena can be represented as multi-agent systems. Over time, these systems have been proven a really powerful tool for modelling and understanding phenomena in fields, such as economics and trading, health care, urban planning and social sciences. However, although, intelligent agents have been around for years, their actual implementation is still in its early stages. Since the late nineties many agent platforms have been developed. Some of them have already been abandoned whereas others continue releasing new versions. On the other hand, the agent-oriented research community is still providing more and more new platforms. This vast amount of platform options leads to a high degree of heterogeneity. Hence, a common problem is how people interested in using multi-agent systems should choose which platform to use in order to benefit from agent technology. This decision was usually left to word of mouth, past experiences or platform publicity, lately however people depend on solid survey articles. To date, in most cases multi-agent system surveys describe only the basic characteristics of a few representatives without even providing any classification of the systems themselves. This article presents a comparative up-to-date review of the most promising existing agent platforms that can be used. It is based on universal comparison and evaluation criteria, proposing classifications for helping readers to understand which agent platforms broadly exhibit similar properties and in which situations which choices should be made.

Suggested Citation

  • Kalliopi Kravari & Nick Bassiliades, 2015. "A Survey of Agent Platforms," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(1), pages 1-11.
  • Handle: RePEc:jas:jasssj:2014-71-2
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    Cited by:

    1. Shobole, Abdulfetah Abdela & Wadi, Mohammed, 2021. "Multiagent systems application for the smart grid protection," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    2. Husáková Martina, 2018. "Use of the Multi-Agent Paradigm in Sustainable Tourism," Czech Journal of Tourism, Sciendo, vol. 7(1), pages 5-24, June.
    3. Sara Bourhime & Mohamed Tkiouat, 2018. "Rethinking Microfinance in a Dual Financial System: An Agent-based Simulation," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 65(1), pages 13-29, March.
    4. Xu, Liming & Mak, Stephen & Brintrup, Alexandra, 2021. "Will bots take over the supply chain? Revisiting agent-based supply chain automation," International Journal of Production Economics, Elsevier, vol. 241(C).
    5. Scheller, Fabian & Johanning, Simon & Bruckner, Thomas, 2019. "A review of designing empirically grounded agent-based models of innovation diffusion: Development process, conceptual foundation and research agenda," Contributions of the Institute for Infrastructure and Resources Management 01/2019, University of Leipzig, Institute for Infrastructure and Resources Management.
    6. Tom Warnke & Oliver Reinhardt & Anna Klabunde & Frans Willekens & Adelinde M. Uhrmacher, 2017. "Modelling and simulating decision processes of linked lives: An approach based on concurrent processes and stochastic race," Population Studies, Taylor & Francis Journals, vol. 71(0), pages 69-83, October.
    7. Chi-Yo Huang & Hui-Ya Wang & Chia-Lee Yang & Steven J. H. Shiau, 2020. "A Derivation of Factors Influencing the Diffusion and Adoption of an Open Source Learning Platform," Sustainability, MDPI, vol. 12(18), pages 1-27, September.
    8. Démare, Thibaut & Bertelle, Cyrille & Dutot, Antoine & Lévêque, Laurent, 2017. "Modeling logistic systems with an agent-based model and dynamic graphs," Journal of Transport Geography, Elsevier, vol. 62(C), pages 51-65.
    9. Woltmann, Stefan & Kittel, Julia, 2022. "Development and implementation of multi-agent systems for demand response aggregators in an industrial context," Applied Energy, Elsevier, vol. 314(C).
    10. Uikyun Na & Eun-Kyu Lee, 2020. "Fog BEMS: An Agent-Based Hierarchical Fog Layer Architecture for Improving Scalability in a Building Energy Management System," Sustainability, MDPI, vol. 12(7), pages 1-28, April.
    11. Steven Manson & Li An & Keith C. Clarke & Alison Heppenstall & Jennifer Koch & Brittany Krzyzanowski & Fraser Morgan & David O'Sullivan & Bryan C Runck & Eric Shook & Leigh Tesfatsion, 2020. "Methodological Issues of Spatial Agent-Based Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 23(1), pages 1-3.
    12. An, Li & Grimm, Volker & Sullivan, Abigail & Turner II, B.L. & Malleson, Nicolas & Heppenstall, Alison & Vincenot, Christian & Robinson, Derek & Ye, Xinyue & Liu, Jianguo & Lindkvist, Emilie & Tang, W, 2021. "Challenges, tasks, and opportunities in modeling agent-based complex systems," Ecological Modelling, Elsevier, vol. 457(C).

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