MultiGain: A controller synthesis tool for MDPs with multiple mean-payoff objectives

[BCFK15] T. Brázdil, K. Chatterjee, V. Forejt, and A. Kučera. MultiGain: A controller synthesis tool for MDPs with multiple mean-payoff objectives. In Christel Baier and Cesare Tinelli (editors), Proceedings of 21st International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2015), volume 9035 of LNCS, pages 181-187, Springer. 2015. [pdf] [bib]

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Notes: A preliminary Arxiv version is available at http://arxiv.org/abs/1501.03093. This tool implements some of the algorithms of [BBC+14]. The original publication is available at link.springer.com.

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Abstract. We present MultiGain, a tool to synthesize strategies for Markov decision processes (MDPs) with multiple mean-payoff objectives. Our models are described in PRISM, and our tool uses the existing interface and simulator of PRISM. Our tool extends PRISM by adding novel algorithms for multiple mean-payoff objectives, and also provides features such as (i)~generating strategies and exploring them for simulation, and checking them with respect to other properties; and (ii)~generating an approximate Pareto curve for two mean-payoff objectives. In addition, we present a new practical algorithm for the analysis of MDPs with multiple mean-payoff objectives under memoryless strategies.