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IADIS
2008

Towards Mining for Influence in a Multi Agent Environment

8 years 4 months ago
Towards Mining for Influence in a Multi Agent Environment
Multi agent learning systems pose an interesting set of problems: in large environments agents may develop localised behaviour patterns that are not necessarily optimal; in a pure agent system there is no globally aware element which can identify and eliminate retrograde behaviour; and as systems scale they may produce large amounts of data, a system may have in the order of 106 cells with 105 agents, each generating data. This position paper introduces research that combines data mining with a logical framework to allow agents in large systems to learn about their environment and develop behaviours appropriate to satisfying system norms. We build from traditional multi agent systems, adding a novel process algebraic approach to co-operation using data mining techniques to identify co-operative behaviours worth learning. The result is predicted to be a learning system in which agents form collectives increasing their `mutual influence' on the environment. KEYWORDS Agent-systems, ...
Robert Logie, Jon G. Hall, Kevin G. Waugh
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where IADIS
Authors Robert Logie, Jon G. Hall, Kevin G. Waugh
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