Hidden-Mode Markov Decision Processes for Nonstationary Sequential Decision Making

The complexity of Markov decision processes

Mathematics of Operations Research

Integrated architecture for learning, planning, and reacting based on approximating dynamic programming

Proceedings of the seventh international conference (1990) on Machine learning

A Survey of solution techniques for the partially observed Markov decision process

Annals of Operations Research

A survey of algorithmic methods for partially observed Markov decision processes

Annals of Operations Research

Reinforcement learning in Markovian and non-Markovian environments

NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3

Exploration bonuses and dual control

Machine Learning

Markov Decision Processes: Discrete Stochastic Dynamic Programming

Markov Decision Processes: Discrete Stochastic Dynamic Programming

Introduction to Reinforcement Learning

Introduction to Reinforcement Learning

Dynamic Programming

Dynamic Programming

Efficient dynamic-programming updates in partially observable Markov decision processes

Efficient dynamic-programming updates in partially observable Markov decision processes

Memory Approaches to Reinforcement Learning in Non-Markovian Domains

Memory Approaches to Reinforcement Learning in Non-Markovian Domains

Algorithms for partially observable markov decision processes

Algorithms for partially observable markov decision processes

Reinforcement learning with selective perception and hidden state

Reinforcement learning with selective perception and hidden state

Reinforcement learning in nonstationary environments

Reinforcement learning in nonstationary environments

Reinforcement learning: a survey

Journal of Artificial Intelligence Research

A model approximation scheme for planning in partially observable stochastic domains

Journal of Artificial Intelligence Research

A method for speeding up value iteration in partially observable Markov decision processes

UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence

Incremental pruning: a simple, fast, exact method for partially observable Markov decision processes

UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence