Multi-agent-stelsel
'n Multi-agent-stelsel (MAS of "self-georganiseerde stelsel") is 'n gerekenariseerde stelsel wat bestaan uit veelvuldige interaktiewe intelligente agente.[1] Multi-agent stelsels kan probleme oplos wat moeilik of onmoontlik is vir 'n individuele agent of 'n monolitiese stelsel om op te los.[2] Intelligensie kan metodiese, funksionele, prosedurele benaderings, algoritmiese soektogte of versterkingsleer insluit.[3] Met vooruitgang in groottaalmodelle (LLM's), het LLM-gebaseerde multi-agent stelsels na vore gekom as 'n nuwe navorsingsgebied, wat meer gesofistikeerde interaksies en koördinasie tussen agente moontlik maak.[4]
Ten spyte van aansienlike oorvleueling, is 'n multi-agent-stelsel nie altyd dieselfde as 'n agent-gebaseerde model (AGM) nie. Die doel van 'n AGM is om te soek na verduidelikende insig in die kollektiewe gedrag van agente (wat nie noodwendig "intelligent hoef te wees nie") deur eenvoudige reëls te gehoorsaam, tipies in natuurlike stelsels, eerder as om spesifieke praktiese of ingenieursprobleme op te los. Die terminologie van AGM is geneig om meer dikwels in die wetenskap gebruik te word, en MAS in ingenieurswese en tegnologie.[5] Toepassings waar multi-agent stelselnavorsing 'n gepaste benadering kan lewer, sluit in aanlynhandel,[6] rampreaksie,[7][8] teikenwaarneming[9] en sosiale struktuurmodellering.[10]
Verwysings
[wysig | wysig bron]- ↑ Yoav Shoham, Kevin Leyton-Brown. Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations. Cambridge University Press, 2009. http://www.masfoundations.org/
- ↑ Hu, J.; Turgut, A.; Lennox, B.; Arvin, F., "Robust Formation Coordination of Robot Swarms with Nonlinear Dynamics and Unknown Disturbances: Design and Experiments" IEEE Transactions on Circuits and Systems II: Express Briefs, 2021.
- ↑ Stefano V. Albrecht, Filippos Christianos, Lukas Schäfer. Multi-Agent Reinforcement Learning: Foundations and Modern Approaches. MIT Press, 2024. https://www.marl-book.com/
- ↑ Li, Guohao (2023). "Camel: Communicative agents for "mind" exploration of large language model society" (PDF). Advances in Neural Information Processing Systems. 36: 51991–52008. arXiv:2303.17760. S2CID 257900712.
- ↑ Niazi, Muaz; Hussain, Amir (2011). "Agent-based Computing from Multi-agent Systems to Agent-Based Models: A Visual Survey" (PDF). Scientometrics. 89 (2): 479–499. arXiv:1708.05872. doi:10.1007/s11192-011-0468-9. hdl:1893/3378. S2CID 17934527.
- ↑ Rogers, Alex; David, E.; Schiff, J.; Jennings, N.R. (2007). "The Effects of Proxy Bidding and Minimum Bid Increments within eBay Auctions". ACM Transactions on the Web. 1 (2): 9–es. CiteSeerX 10.1.1.65.4539. doi:10.1145/1255438.1255441. S2CID 207163424. Geargiveer vanaf die oorspronklike op 2 April 2010. Besoek op 18 Maart 2008.
- ↑ Schurr, Nathan; Marecki, Janusz; Tambe, Milind; Scerri, Paul; Kasinadhuni, Nikhil; Lewis, J.P. (2005). "The Future of Disaster Response: Humans Working with Multiagent Teams using DEFACTO". Geargiveer (PDF) vanaf die oorspronklike op 3 Junie 2013. Besoek op 8 Januarie 2024.
- ↑ Genc, Zulkuf; et al. (2013). "Agent-Based Information Infrastructure for Disaster Management" (PDF). Intelligent Systems for Crisis Management. Lecture Notes in Geoinformation and Cartography. pp. 349–355. doi:10.1007/978-3-642-33218-0_26. ISBN 978-3-642-33217-3.
- ↑ Hu, Junyan; Bhowmick, Parijat; Lanzon, Alexander (2020). "Distributed Adaptive Time-Varying Group Formation Tracking for Multiagent Systems With Multiple Leaders on Directed Graphs". IEEE Transactions on Control of Network Systems. 7: 140–150. doi:10.1109/TCNS.2019.2913619. S2CID 149609966.
- ↑ Sun, Ron; Naveh, Isaac (30 Junie 2004). "Simulating Organizational Decision-Making Using a Cognitively Realistic Agent Model". Journal of Artificial Societies and Social Simulation.
