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Erschienen in:
2019 | OriginalPaper | Buchkapitel
SPI: A Software Tool for Planning Under Uncertainty Based on Learning Factored MDPs
verfasst von : Alberto Reyes, Pablo H. Ibargüengoytia, Guillermo Santamaría
Erschienen in: Advances in Soft Computing
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Abstract
In this paper the SPI system is presented. SPI is a software tool for planning under uncertainty based on learning Markov Decision Processes. A brief review of some similar tools as well as the scientific basis of factored representations and some of its variants are included. Among these variants are qualitative representations and hybrid qualitative-discrete representations that are the core of the software tool. The functional structure of SPI, which is composed of four main modules, is also described. These modules are: the compiler, the policy server, a format translator and a didactic simulator. The experimental results obtained when testing SPI in a robot navigation domain using different types of representations and different state partitions demonstrated its capability to reduce state spaces.