A Correctness Result for Synthesizing Plans With Loops in Stochastic Domains

Laszlo Treszkai, Vaishak Belle

Research output: Contribution to journalArticlepeer-review


Finite-state controllers (FSCs), such as plans with loops, are powerful and compact representations of action selection widely used in robotics, video games and logistics. There has been steady progress on synthesizing FSCs in deterministic environments, but the algorithmic machinery needed for lifting such techniques to stochastic environments is not yet fully understood. While the derivation of FSCs has received some attention in the context of discounted expected reward measures, they are often solved approximately and/or without correctness guarantees. In essence, that makes it difficult to analyze fundamental concerns such as: do all paths terminate, and do the majority of paths reach a goal state?
In this paper, we present new theoretical results on a generic technique for synthesizing FSCs in stochastic environments, allowing for highly granular specifications on termination and goal satisfaction.
Original languageEnglish
Pages (from-to)92-107
Number of pages19
JournalInternational Journal of Approximate Reasoning
Early online date19 Dec 2019
Publication statusPublished - 30 Apr 2020
Event30th International Conference on Automated Planning and Scheduling - Nancy, France
Duration: 26 Oct 202030 Oct 2020


  • Plan and program synthesis
  • Stochastic domains
  • Loops in plans and programs
  • Stochastic algorithms
  • Planning in robotics

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