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arXiv · 1702.08441

Monte Carlo Action Programming

Lenz Belzner
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Abstract

This paper proposes Monte Carlo Action Programming, a programming language framework for autonomous systems that act in large probabilistic state spaces with high branching factors. It comprises formal syntax and semantics of a nondeterministic action programming language. The language is interpreted stochastically via Monte Carlo Tree Search. Effectiveness of the approach is shown empirically.

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Lenz Belzner. 2017-02-25. Monte Carlo Action Programming. https://arxiv.org/abs/1702.08441

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