Identification of Unexpected Decisions in Partially Observable Monte-Carlo Planning: a Rule-Based Approach.
Giulio MazziAlberto CastelliniAlessandro FarinelliPublished in: CoRR (2020)
Keyphrases
- monte carlo
- partially observable
- state space
- decision problems
- markov decision processes
- reinforcement learning
- dynamical systems
- partial observability
- markov chain
- markov decision problems
- infinite horizon
- partial observations
- planning domains
- monte carlo simulation
- particle filter
- importance sampling
- belief state
- belief space
- decision makers
- decision making
- monte carlo tree search
- optimal strategy
- reward function
- orders of magnitude
- planning problems
- heuristic search
- temporal difference
- linear programming
- partially observable markov decision processes
- decision process
- dynamic programming