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Optimal Policies for Partially Observable Markov Decision Processes

Anthony R. Cassandra

发表年份
1994
引用次数
68

摘要

this paper, we will be exploring a specific model-based scheme in which decisions need to be made. Even when we cannot assume we have the model, we can use techniques, [2], that allow us to approximate the model and then apply these model-based schemes. The many problems associated with such models will be outlined in a subsequent section. Throughout this discussion, the term agent will refer to the automated process that has to make decisions. A convenient example of an agent is that of an autonomous robot trying to survive in a real world environment. However, the agent can simply be a computer program such as one that does medical diagnosis. In this case, the model of the world might be based upon statistics and medical research.

关键词

Partially observable Markov decision processObservableMarkov decision processComputer scienceWitnessMathematical optimizationMarkov processMarkov chainAlgorithmMarkov model

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