Learning and Exploiting Context in Agents

CPM Report No.: 01-85
By: Bruce Edmonds
Date: 7th November 2001

Published as: Edmonds, B. (2002) Learning and Exploiting Context in Agents. First International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2002), Bologna, Italy, July 2002. ACM Press, 1231-1238.


The use of context can considerably facilitate reasoning by restricting the beliefs reasoned upon to those relevant and providing extra information specific to the context.  Despite the use and formalization of context being extensively studied both in AI and ML, context has not been much  utilized in agents.  This may be because many agents are only applied in a single context, and so these aspects are implicit in their design, or it may be that the need to explicitly encode information about various contexts is onerous.  An algorithm to learn the appropriate context along with knowledge relevant to that context gets around these difficulties and opens the way for the exploitation of context in agent design.  The algorithm is described and the agents compared with agents that learn and apply knowledge in a generic way within an artificial stock market.  The potential for context as a principled manner of closely integrating crisp reasoning and fuzzy learning is discussed.

Keywords: Context, integration, learning, deduction, genetic programming, evolutionary computation, cognitive analogy, biological analogy, agents, multi-agent system.

The Paper is Accessible as:

The slides from the AAMAS 2002 talk: