Context-mediated behavior for intelligent agents

Humans and other animals are exquisitely attuned to their context. Context affects almost all aspects of behavior, and it does so for the most part automatically, without a conscious reasoning effort. This would be a very useful property for an artificial agent to have: upon recognizing its context, the agent's behavior would automatically adjust to fit it. This paper describescontext-mediated behavior(CMB), an approach to context-sensitive behavior we have developed over the past few years for intelligent autonomous agents. In CMB, contexts are represented explicitly ascontextual schemas(c-schemas). An agent recognizes its context by finding the c-schemas that match it, then it merges these to form a coherent representation of the current context. This includes not only a description of the context, but also information about how to behave in it. From that point until the next context change, knowledge for context-sensitive behavior is available with no additional effort. This is used to influence perception, make predictions about the world, handle unanticipated events, determine the context-dependent meaning of concepts, focus attention and select actions. CMB is being implemented in the Orca program, an intelligent controller for autonomous underwater vehicles.

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