Answer set programming for non-stationary Markov decision processes.
Leonardo Anjoletto FerreiraReinaldo A. C. BianchiPaulo E. SantosRamón López de MántarasPublished in: Appl. Intell. (2017)
Keyphrases
- non stationary
- answer set programming
- markov decision processes
- logic programs
- logic programming
- answer sets
- finite state
- optimal policy
- state space
- policy iteration
- reinforcement learning
- transition matrices
- decision theoretic planning
- dynamic programming
- planning under uncertainty
- empirical mode decomposition
- finite horizon
- answer set programs
- markov decision process
- infinite horizon
- reward function
- knowledge representation
- partially observable markov decision processes
- average cost
- average reward
- data mining
- real time dynamic programming
- knowledge base
- artificial intelligence