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: