Publication Details
Fuel in Markov Decision Processes (FiMDP): A Practical Approach to Consumption
Blahoudek František, RNDr., Ph.D. (DITS FIT BUT)
Cubuktepe Murat (UTAUSTIN)
Ornik Melkior (UILLINOIS)
Thangeda Pranay (UILLINOIS)
Topcu Ufuk (UTAUSTIN)
Behavioral research, Decision making, Model checking, Multi agent systems, Polynomial approximation
Consumption Markov Decision Processes (CMDPs) are probabilistic decision-making models of resource-constrained systems. We introduce FiMDP, a tool for controller synthesis in CMDPs with LTL objectives expressible by deterministic Büchi automata. The tool implements the recent algorithm for polynomial-time controller synthesis in CMDPs, but extends it with many additional features. On the conceptual level, the tool implements heuristics for improving the expected reachability times of accepting states, and a support for multi-agent task allocation. On the practical level, the tool offers (among other features) a new strategy simulation framework, integration with the Storm model checker, and FiMDPEnv - a new set of CMDPs that model real-world resource-constrained systems. We also present an evaluation of FiMDP on these real-world scenarios.
@INPROCEEDINGS{FITPUB13361, author = "Petr Novotn\'{y} and Franti\v{s}ek Blahoudek and Murat Cubuktepe and Melkior Ornik and Pranay Thangeda and Ufuk Topcu", title = "Fuel in Markov Decision Processes (FiMDP): A Practical Approach to Consumption", pages = "640--656", booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)", year = 2021, location = "Pittsburgh, US", ISBN = "978-3-030-90869-0", doi = "10.1007/978-3-030-90870-6\_34", language = "english", url = "https://www.fit.vut.cz/research/publication/13361" }