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
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991