Machine Learning for Logic-Based Multi-agent Systems

Eduardo Alonso; Daniel Kudenko

doi:10.1007/3-540-45484-5_28

Machine Learning for Logic-Based Multi-agent Systems

Eduardo Alonso, Daniel Kudenko

Computer Science

Research output: Contribution to conference › Paper › peer-review

Abstract

When developing a Multi-Agent System (MAS), it is very difficult and sometimes even impossible to foresee all potential situations the agents could encounter and specify their behaviour in advance. Therefore it is widely recognised that one of the more important features of high level agents is their capability to adapt and learn.

Original language	Undefined/Unknown
Pages	306-307
DOIs	https://doi.org/10.1007/3-540-45484-5_28
Publication status	Published - 2000

Access to Document

10.1007/3-540-45484-5_28

http://link.springer.de/link/service/series/0558/bibs/1871/18710306.htm

Cite this

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title = "Machine Learning for Logic-Based Multi-agent Systems",

abstract = "When developing a Multi-Agent System (MAS), it is very difficult and sometimes even impossible to foresee all potential situations the agents could encounter and specify their behaviour in advance. Therefore it is widely recognised that one of the more important features of high level agents is their capability to adapt and learn. ",

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