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- W2063722002 abstract "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." @default.
- W2063722002 created "2016-06-24" @default.
- W2063722002 creator A5005548767 @default.
- W2063722002 date "2002-01-01" @default.
- W2063722002 modified "2023-10-17" @default.
- W2063722002 title "Learning and exploiting context in agents" @default.
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- W2063722002 doi "https://doi.org/10.1145/545056.545105" @default.
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