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- W4240765353 abstract "Traditionally multi-agent learning is considered as the intersection of two subfields of artificial intelligence: multi-agent systems and machine learning. Conventional machine learning involves a single agent that is trying to maximise some utility function without any awareness of existence of other agents in the environment (Mitchell, 1997). Meanwhile, multi-agent systems consider mechanisms for the interaction of autonomous agents. Learning system is defined as a system where an agent learns to interact with other agents (e.g., Clouse, 1996; Crites & Barto, 1998; Parsons, Wooldridge & Amgoud, 2003). There are two problems that agents need to overcome in order to interact with each other to reach their individual or shared goals: since agents can be available/unavailable (i.e., they might appear and/or disappear at any time), they must be able to find each other, and they must be able to interact (Jennings, Sycara & Wooldridge, 1998)." @default.
- W4240765353 created "2022-05-12" @default.
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- W4240765353 date "2011-05-24" @default.
- W4240765353 modified "2023-09-27" @default.
- W4240765353 title "Learning Systems Engineering" @default.
- W4240765353 doi "https://doi.org/10.4018/978-1-59904-935-9.ch114" @default.
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