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Modelling other agents through evolutionary behaviours
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DOI：10.1007/s12293-021-00343-8.png)
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摘要
En 中文
Modelling other agents is a challenging topic in artificial intelligence research particularly when a subject agent needs to optimise its own decisions by predicting their behaviours under uncertainty. Existing research often leads to a monotonic set of behaviours for other agents so that a subject agent can not cope with unexpected decisions from the other agents. It requires creative ideas about developing diversity of behaviours so as to improve the subject agent's decision quality. In this paper, we resort to evolutionary computation approaches to generate a new set of behaviours for other agents and solve the complicated agents' behaviour search and evaluation issues. The new approach starts with the initial behaviours that are ascribed to the other agents and expands the behaviours by using a number of genetic operators in the behaviour evolution. This is the first time that evolutionary techniques are used to modelling other agents in a general multiagent decision framework. We examine the new methods in two well-studied problem domains and provide experimental results in support.
Keyword:
Intelligent agents
Evolutionary computation
Planning and decision making
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期刊
IF:
2.3
论文数:
456
被引数:
718
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Autonomous agents modelling other agents: A comprehensive survey and open problems自治代理对其他代理进行建模: 全面调查和开放问题OAAI
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