Life Is Random, Time Is Not: Markov Decision Processes with Window Objectives.
Thomas BrihayeFlorent DelgrangeYoussouf OualhadjMickael RandourPublished in: CONCUR (2019)
Keyphrases
- markov decision processes
- optimal policy
- finite state
- state space
- policy iteration
- dynamic programming
- transition matrices
- reinforcement learning
- planning under uncertainty
- reinforcement learning algorithms
- average cost
- finite horizon
- decision theoretic planning
- markov decision process
- risk sensitive
- reachability analysis
- decision processes
- average reward
- partially observable
- infinite horizon
- state and action spaces
- action sets
- discounted reward
- semi markov decision processes
- action space
- decision diagrams
- continuous state spaces
- factored mdps
- multiple objectives
- model based reinforcement learning
- real valued
- stochastic shortest path