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On Ability to Autonomously Execute Agent Programs with Sensing

By Sebastian Sardiña, Yves Lespérance and Hector J. Levesque


Most existing work in agent programming assumes an execution model where an agent has a knowledge base (KB) about the current state of the world, and makes decisions about what to do in terms of what is entailed or consistent with this KB. We show that in the presence of sensing, such a model does not always work properly, and propose an alternative that does. We then discuss how this affects agent programming language design/semantics. 1

Year: 2009
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