Preference Planning for Markov Decision Processes.
Meilun LiZhikun SheAndrea TurriniLijun ZhangPublished in: AAAI (2015)
Keyphrases
- markov decision processes
- macro actions
- planning under uncertainty
- decision theoretic planning
- partially observable
- state space
- optimal policy
- finite state
- reinforcement learning
- dynamic programming
- probabilistic planning
- transition matrices
- finite horizon
- partially observable markov decision processes
- planning problems
- heuristic search
- policy iteration
- reachability analysis
- risk sensitive
- reinforcement learning algorithms
- markov decision process
- state and action spaces
- average cost
- decision theoretic
- blocks world
- average reward
- decision processes
- factored mdps
- dynamical systems
- model based reinforcement learning
- infinite horizon
- markov decision problems
- action space
- discounted reward
- reward function
- ai planning