Cited by 133Multi-Agent Systems and NegotiationAI-based Problem Solving and PlanningLogic, Reasoning, and Knowledge

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A Review of Agent-Based Programming for Multi-Agent Systems

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Abstract

Intelligent and autonomous agents is a subarea of symbolic artificial intelligence where these agents decide, either reactively or proactively, upon a course of action by reasoning about the information that is available about the world (including the environment, the agent itself, and other agents). It encompasses a multitude of techniques, such as negotiation protocols, agent simulation, multi-agent argumentation, multi-agent planning, and many others. In this paper, we focus on agent programming and we provide a systematic review of the literature in agent-based programming for multi-agent systems. In particular, we discuss both veteran (still maintained) and novel agent programming languages, their extensions, work on comparing some of these languages, and applications found in the literature that make use of agent programming.

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  1. Wooldridge, M. (2009). An Introduction to MultiAgent Systems, John Wiley and Sons. [2nd ed.].
  2. Logan, 2018, An agent programming manifesto, Int. J. Agent-Oriented Softw. Eng., 6, 187, 10.1504/IJAOSE.2018.094374 · DOI
  3. Russell, S.J., and Norvig, P. (2010). Artificial Intelligence: A Modern Approach, Prentice Hall. [3rd ed.].
  4. Bordini, 2020, Agent programming in the cognitive era, Auton. Agents Multi Agent Syst., 34, 37, 10.1007/s10458-020-09453-y · DOI
  5. Mao, 2017, A survey of agent-oriented programming from software engineering perspective, Web Intell., 15, 143, 10.3233/WEB-170357 · DOI
  6. Kravari, K., and Bassiliades, N. (2015). A Survey of Agent Platforms. J. Artif. Soc. Soc. Simul., 18. · DOI · Paper page
  7. Abar, 2017, Agent Based Modelling and Simulation tools: A review of the state-of-art software, Comput. Sci. Rev., 24, 13, 10.1016/j.cosrev.2017.03.001 · DOI
  8. Isern, 2016, A systematic literature review of agents applied in healthcare, J. Med Syst., 40, 43, 10.1007/s10916-015-0376-2 · DOI
  9. Shoham, 1993, Agent-oriented Programming, Artif. Intell., 60, 51, 10.1016/0004-3702(93)90034-9 · DOI
  10. Georgeff, 1986, Procedural Knowledge, Proc. IEEE (Spec. Issue Knowl. Represent.), 74, 1383
  11. Rao, A.S., and Georgeff, M. (1995, January 12–14). BDI Agents: From Theory to Practice. Proceedings of the First International Conference on Multiagent Systems (ICMAS), San Francisco, CA, USA.
  12. Perram, 1996, AgentSpeak(L): BDI Agents Speak Out in a Logical Computable Language, Agents Breaking Away, Proceedings of the 7th European Workshop on Modelling Autonomous Agents in a Multi-Agent World, Eindhoven, The Netherlands, 22–25 January 1996, Volume 1038, 42
  13. Meltzer, B., and Michie, D. (1969). Some Philosophical Problems from the Standpoint of Artificial Intelligence. Machine Intelligence 4, Edinburgh University Press.
  14. Issicaba, D., Rosa, M.A., Prostejovsky, A.M., and Bindner, H.W. (2017, January 26–29). Experimental validation of BDI agents for distributed control of electric power grids. Proceedings of the 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), Torino, Italy. · DOI
  15. Sorici, A., Boissier, O., Picard, G., and Santi, A. (2011, January 1–31). Exploiting the JaCaMo Framework for Realising an Adaptive Room Governance Application. Proceedings of the Compilation of the Co-Located Workshops on DSM’11, TMC’11, AGERE! 2011, AOOPES’11, NEAT’11, and VMIL’11, New York, NY, USA. · DOI
  16. Demazeau, Y., Müller, J.P., Rodríguez, J.M.C., and Pérez, J.B. (2012). A JaCaMo-Based Governance of Machine-to-Machine Systems. Advances on Practical Applications of Agents and Multi-Agent Systems, Springer. · DOI
  17. Krupa, 2012, Handling Privacy as Contextual Integrity in Decentralized Virtual Communities: The PrivaCIAS Framework, Web Intelli. Agent Syst., 10, 105, 10.3233/WIA-2012-0235 · DOI
  18. Chen, 2015, Reflecting on Agent Programming with AgentSpeak(L), Proceedings of the PRIMA 2015: Principles and Practice of Multi-Agent Systems—18th International Conference, Bertinoro, Italy, 26–30 October 2015, Volume 9387, 351
  19. Millar, 2019, Chromar, a language of parameterised agents, Theor. Comput. Sci., 765, 97, 10.1016/j.tcs.2017.07.034 · DOI
  20. Hindriks, K.V., de Boer, F.S., van der Hoek, W., and Meyer, J.J.C. (2020, January 7–9). Agent Programming with Declarative Goals. Proceedings of the 7th International Workshop on Agent Theories, Architectures, Boston, MA, USA.
  21. Bordini, R.H., Wooldridge, M., and Hübner, J.F. (2007). Programming Multi-Agent Systems in AgentSpeak Using Jason, John Wiley & Sons. · DOI
  22. Boissier, 2013, Multi-agent oriented programming with JaCaMo, Sci. Comput. Program., 78, 747, 10.1016/j.scico.2011.10.004 · DOI · Paper page
  23. Boissier, O., Bordini, R., Hubner, J., and Ricci, A. (2020). Multi-Agent Oriented Programming: Programming Multi-Agent Systems Using JaCaMo, MIT Press. · DOI
  24. Ricci, A., Piunti, M., Viroli, M., and Omicini, A. (2009). Environment Programming in CArtAgO. Multi-Agent Programming: Languages, Tools and Applications, Springer. Chapter 8. · DOI
  25. Sichman, 2007, Developing organised multiagent systems using the MOISE+ model: Programming issues at the system and agent levels, Int. J. Agent-Oriented Softw. Eng., 1, 370, 10.1504/IJAOSE.2007.016266 · DOI
  26. Bellifemine, F.L., Caire, G., and Greenwood, D. (2007). Developing Multi-Agent Systems with JADE (Wiley Series in Agent Technology), John Wiley & Sons. · DOI
  27. Bergenti, 2017, Agent-oriented model-driven development for JADE with the JADEL programming language, Comput. Lang. Syst. Struct., 50, 142
  28. Bergenti, F., Monica, S., and Petrosino, G. (2018, January 5). A scripting language for practical agent-oriented programming. Proceedings of the 8th ACM SIGPLAN International Workshop on Programming Based on Actors, Agents, and Decentralized Control, AGERE!@SPLASH 2018, Boston, MA, USA. · DOI
  29. Pokahr, A., Braubach, L., and Lamersdorf, W. (2005). Jadex: A BDI Reasoning Engine. Multi-Agent Programming: Languages, Platforms and Applications, Springer. · DOI
  30. Aschermann, M., Dennisen, S., Kraus, P., and Müller, J.P. (2018, January 10–15). LightJason, a Highly Scalable and Concurrent Agent Framework: Overview and Application. Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, AAMAS 2018, Stockholm, Sweden.
  31. Hashmi, M.A., Seghrouchni, A.E.F., and Akram, M.U. (2015, January 6–9). A Planning Based Agent Programming Language Supporting Environment Modeling. Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2015, Singapore. · DOI
  32. Kilaru, J. (2018). PLASA: Programming Language for Synchronous Agents. [Master’s Thesis, California State University].
  33. Flocchini, 2005, Gathering of asynchronous robots with limited visibility, Theor. Comput. Sci., 337, 147, 10.1016/j.tcs.2005.01.001 · DOI
  34. Bonci, A., Pirani, M., Bianconi, C., and Longhi, S. (2018, January 2–4). RMAS: Relational Multiagent System for CPS Prototyping and Programming. Proceedings of the 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, MESA 2018, Oulu, Finland. · DOI
  35. Rodriguez, S., Gaud, N., and Galland, S. (2014, January 11–14). SARL: A General-Purpose Agent-Oriented Programming Language. Proceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), Warsaw, Poland. · DOI
  36. Molesini, 2013, Simulation in agent-oriented software engineering: The SODA case study, Sci. Comput. Program., 78, 705, 10.1016/j.scico.2011.09.007 · DOI
  37. Moreno, 2015, PEABS: A Process for developing Efficient Agent-Based Simulators, Eng. Appl. Artif. Intell., 46, 104, 10.1016/j.engappai.2015.09.003 · DOI
  38. Pavón, J., Gómez-Sanz, J., and Fuentes-Fernández, R. (2005). The INGENIAS methodology and tools. Agent-Oriented Methodol, IGI Global. · DOI
  39. Caillou, P., Gaudou, B., Grignard, A., Truong, Q.C., and Taillandier, P. (2015, January 14–18). A Simple-to-Use BDI Architecture for Agent-Based Modeling and Simulation. Proceedings of the European Social Simulation Association 2015, Groningen, The Netherlands.
  40. Taillandier, P., Bourgais, M., Caillou, P., Adam, C., and Gaudou, B. (2016, January 10). A BDI Agent Architecture for the GAMA Modeling and Simulation Platform. Proceedings of the Multi-Agent Based Simulation XVII—International Workshop, MABS 2016, Singapore. · DOI
  41. Singh, 2016, Integrating BDI Agents with Agent-Based Simulation Platforms, Auton. Agents Multi Agent Syst., 30, 1050, 10.1007/s10458-016-9332-x · DOI
  42. Belle, V., and Levesque, H.J. (2014, January 27–31). PREGO: An Action Language for Belief-Based Cognitive Robotics in Continuous Domains. Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, Québec City, QC, Canada. · DOI
  43. Belle, V., and Levesque, H.J. (2015, January 25–31). ALLEGRO: Belief-Based Programming in Stochastic Dynamical Domains. Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI 2015, Buenos Aires, Argentina.
  44. Levesque, 1997, GOLOG: A Logic Programming Language for Dynamic Domains, J. Log. Program., 31, 59, 10.1016/S0743-1066(96)00121-5 · DOI
  45. Ferrein, A., Maier, C., Mühlbacher, C., Niemueller, T., Steinbauer, G., and Vassos, S. (2016, January 22–24). Controlling Logistics Robots with the Action-Based Language YAGI. Proceedings of the Intelligent Robotics and Applications—9th International Conference, ICIRA 2016, Tokyo, Japan. · DOI
  46. Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., Wheeler, R., and Ng, A. (2009, January 12–13). ROS: An open-source Robot Operating System. Proceedings of the Workshop on Open Source Software at the International Conference on Robotics and Automation, Kobe, Japan.
  47. Kaptein, F., Broekens, J., Hindriks, K.V., and Neerincx, M.A. (2016, January 20–23). CAAF: A Cognitive Affective Agent Programming Framework. Proceedings of the Intelligent Virtual Agents—16th International Conference, IVA 2016, Los Angeles, CA, USA. · DOI
  48. Ramos, 2003, MASCEM: A multiagent system that simulates competitive electricity markets, IEEE Intell. Syst., 18, 54, 10.1109/MIS.2003.1249170 · DOI
  49. Santos, 2016, MASCEM: Optimizing the performance of a multi-agent system, Energy, 111, 513, 10.1016/j.energy.2016.05.127 · DOI
  50. Navarro, 2017, TABSAOND: A technique for developing agent-based simulation apps and online tools with nondeterministic decisions, Simul. Model. Pract. Theory, 77, 84, 10.1016/j.simpat.2017.05.006 · DOI
  51. Cich, G., Galland, S., Knapen, L., Yasar, A., Bellemans, T., and Janssens, D. (2017, January 21–23). Addressing the Challenges of Conservative Event Synchronization for the SARL Agent-Programming Language. Proceedings of the Advances in Practical Applications of Cyber-Physical Multi-Agent Systems, PAAMS Collection—15th International Conference, PAAMS 2017, Porto, Portugal. · DOI
  52. Jain, 2016, Programming an expressive autonomous agent, Expert Syst. Appl., 43, 131, 10.1016/j.eswa.2015.08.037 · DOI
  53. Jain, 2015, EMIA: Emotion model for intelligent agent, J. Intell. Syst., 24, 449
  54. Dastani, 2008, 2APL: A practical agent programming language, Auton. Agents Multi-Agent Syst., 16, 214, 10.1007/s10458-008-9036-y · DOI
  55. Pantoja, C.E., Stabile, M.F., Lazarin, N.M., and Sichman, J.S. (2016, January 9–10). ARGO: An Extended Jason Architecture that Facilitates Embedded Robotic Agents Programming. Proceedings of the Engineering Multi-Agent Systems—4th International Workshop, EMAS 2016, Singapore. · DOI
  56. Leask, S., and Logan, B. (2015, January 26–30). Programming deliberation strategies in meta-APL. Proceedings of the International Conference on Principles and Practice of Multi-Agent Systems, Bertinoro, Italy. · DOI
  57. Doan, T.T., Yao, Y., Alechina, N., and Logan, B. (2014, January 5–9). Verifying heterogeneous multi-agent programs. Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, AAMAS ’14, Paris, France.
  58. Cardoso, R.C., Ferrando, A., Dennis, L.A., and Fisher, M. (2020, January 14–15). An Interface for Programming Verifiable Autonomous Agents in ROS. Proceedings of the European Conference on Multi-Agent Systems (EUMAS), Thessaloniki, Greece. · DOI
  59. Onyedinma, C., Gavigan, P., and Esfandiari, B. (2020). Toward Campus Mail Delivery Using BDI. J. Sens. Actuator Netw., 9. · DOI
  60. Bosello, M., and Ricci, A. (2019, January 13–14). From Programming Agents to Educating Agents - A Jason-Based Framework for Integrating Learning in the Development of Cognitive Agents. Proceedings of the Engineering Multi-Agent Systems—7th International Workshop, EMAS 2019, Montreal, QC, Canada.
  61. Cardoso, R.C., Zatelli, M.R., Hübner, J.F., and Bordini, R.H. (2013, January 27). Towards Benchmarking Actor- and Agent-Based Programming Languages. Proceedings of the Workshop on Programming Based on Actors, Agents, and Decentralized Control, Indianapolis, IN, USA. · DOI
  62. Challenger, 2016, A systematic approach to evaluating domain-specific modeling language environments for multi-agent systems, Softw. Qual. J., 24, 755, 10.1007/s11219-015-9291-5 · DOI
  63. Bergenti, F., Iotti, E., Monica, S., and Poggi, A. (2017, January 24–26). A Comparison between Asynchronous Backtracking Pseudocode and its JADEL Implementation. Proceedings of the 9th International Conference on Agents and Artificial Intelligence, ICAART, Porto, Portugal. · DOI
  64. Rousset, 2016, A survey on parallel and distributed multi-agent systems for high performance computing simulations, Comput. Sci. Rev., 22, 27, 10.1016/j.cosrev.2016.08.001 · DOI
  65. Sun, 2016, Simple or complicated agent-based models? A complicated issue, Environ. Model. Softw., 86, 56, 10.1016/j.envsoft.2016.09.006 · DOI
  66. Cardoso, 2018, SMART-JaCaMo: An organization-based team for the multi-agent programming contest, Ann. Math. Artif. Intell., 84, 75, 10.1007/s10472-018-9584-z · DOI
  67. Ahlbrecht, T., Dix, J., and Fiekas, N. (2019). SMART–JaCaMo: An Organisation-Based Team for the Multi-Agent Programming Contest. The Multi-Agent Programming Contest 2018, Springer International Publishing. · DOI
  68. Cardoso, R.C., Ferrando, A., and Papacchini, F. (2019). LFC: Combining Autonomous Agents and Automated Planning in the Multi-Agent Programming Contest. Multi-Agent Progamming Contest, Springer.
  69. Ahlbrecht, T., Dix, J., Fiekas, N., and Krausburg, T. (2020). The Requirement Gatherers’ Approach to the 2019 Multi-Agent Programming Contest Scenario. The Multi-Agent Programming Contest 2019, Springer International Publishing. · DOI
  70. Ahlbrecht, T., Dix, J., and Fiekas, N. (2019). Multi-Agent Programming Contest 2018—The Jason-DTU Team. The Multi-Agent Programming Contest 2018, Springer International Publishing. · DOI
  71. Ahlbrecht, T., Dix, J., Fiekas, N., and Krausburg, T. (2020). GOAL-DTU: Development of Distributed Intelligence for the Multi-Agent Programming Contest. The Multi-Agent Programming Contest 2019, Springer International Publishing. · DOI
  72. Wolfram, C. (2020). An Agent-Based Model of COVID-19. Complex Syst., 29. · DOI
  73. Prudhomme, C., Cruz, C., and Cherifi, H. (2020, January 14–15). An Agent based model for the transmission and control of the COVID-19 in Dijon (extended abstract). Proceedings of the MARAMI 2020—Modèles & Analyse des Réseaux: Approches Mathématiques & Informatiques—The 11th Conference on Network Modeling and Analysis, Virtual Conference, Montpellier, France.
  74. Khan, 2017, The research on multi-agent system for microgrid control and optimization, Renew. Sustain. Energy Rev., 80, 1399, 10.1016/j.rser.2017.05.279 · DOI
  75. Kantamneni, 2015, Survey of multi-agent systems for microgrid control, Eng. Appl. Artif. Intell., 45, 192, 10.1016/j.engappai.2015.07.005 · DOI
  76. QuanLi, 2015, Agent-based modeling and simulations of land-use and land-cover change according to ant colony optimization: A case study of the Erhai Lake Basin, China, Nat. Hazards, 75, 95, 10.1007/s11069-014-1303-4 · DOI
  77. North, 2013, Complex Adaptive Systems Modeling with Repast Simphony, Complex Adapt. Syst. Model., 1, 1, 10.1186/2194-3206-1-3 · DOI
  78. Mariethoz, 2015, An agent-based platform for simulating complex human-aquifer interactions in managed groundwater systems, Environ. Model. Softw., 73, 305, 10.1016/j.envsoft.2015.08.018 · DOI
  79. Savaglio, C., Fortino, G., Ganzha, M., Paprzycki, M., Badica, C., and Ivanovic, M. (2017, January 11–13). Agent-Based Computing in the Internet of Things: A Survey. Proceedings of the Intelligent Distributed Computing XI—11th International Symposium on Intelligent Distributed Computing—IDC 2017, Belgrade, Serbia. · DOI
  80. Krivic, P., Skocir, P., Kusek, M., and Jezic, G. (2017, January 21–23). Microservices as Agents in IoT Systems. Proceedings of the Agent and Multi-Agent Systems: Technology and Applications, 11th KES International Conference, KES-AMSTA 2017, Vilamoura, Algarve, Portugal. · DOI
  81. Ayala, 2015, A Software Product Line Process to Develop Agents for the IoT, Sensors, 15, 15640, 10.3390/s150715640 · DOI
  82. Iotti, E., Petrosino, G., Monica, S., and Bergenti, F. (2020, January 4). Exploratory Experiments on Programming Autonomous Robots in Jadescript. Proceedings of the First Workshop on Agents and Robots for reliable Engineered Autonomy, AREA@ECAI 2020, Virtual Event, Santiago de Compostela, Spain. · DOI

Cited by

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Metadata

Authors
Cardoso, R. C., & Ferrando, A.
Affiliations
University of Manchester (GB)
Corresponding author
  • Cardoso, Rafael C.
  • Ferrando, Angelo
Venue
Computers
Publisher
MDPI AG
Published
2021-01-27
Volume
10
Issue
2
Pages
16
ISSN
2073-431X (ISSN-L)
OpenAlex
W3121694942
Cited by
133
References
4
Citations by year
2026: 25 · 2025: 34 · 2024: 19 · 2023: 30 · 2022: 16 · 2021: 9
FWCI
6.54
Type
journal article
Language
en
Open access
Locations
  • Computers (publishedVersion, cc-by)
  • IRIS UNIMORE (University of Modena and Reggio Emilia) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • CINECA IRIS Institutial Research Information System (University of Genoa) (submittedVersion)
Funders
UK Industrial Strategy Challenge Fund, UK Research and Innovation, Engineering and Physical Sciences Research Council (EP/R026084/1, EP/R026092/1, EP/R026173/1)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Multi-Agent Systems and Negotiation
  • Physical Sciences › Computer Science › Artificial Intelligence › AI-based Problem Solving and Planning
  • Physical Sciences › Computer Science › Artificial Intelligence › Logic, Reasoning, and Knowledge
Keywords
agent-oriented programming, multi-agent systems, agent programming languages, cross-linguistic comparison, multi-agent planning, negotiation protocols, agent-based modeling

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Cardoso, R. C., & Ferrando, A. (2021). A Review of Agent-Based Programming for Multi-Agent Systems. Computers. https://doi.org/10.3390/computers10020016