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Basis Construction and Utilization for Markov Decision Processes Using Graphs
Markov decision process Reinforcement learning Representation discovery
2014/12/18
The ease or difficulty in solving a problemstrongly depends on the way it is represented. For example, consider the task of multiplying the numbers 12 and 24. Now imagine multiplying XII and XXIV. Bot...
Increasing Scalability in Algorithms for Centralized and Decentralized Partially Observable Markov Decision Processes: Efficient Decision-Making and Coordination in Uncertain Environments
Artificial Intelligence Decision Theory Game Theory Machine Learning Multiagent Systems Reasoning Under Uncertainty
2014/12/18
As agents are built for ever more complex environments, methods that consider the uncertainty in the system have strong advantages. This uncertainty is common in domains such as robot navigation, medi...
Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions
Online Learning Markov Decision Processes Adversarially Chosen Transition Probability Distributions
2013/5/2
We study the problem of learning Markov decision processes with finite state and action spaces when the transition probability distributions and loss functions are chosen adversarially and are allowed...
Experimental design for Partially Observed Markov Decision Processes
Experimental design Partially Observed Markov Decision Processes
2012/11/22
This paper deals with the question of how to most effectively conduct experiments in Partially Observed Markov Decision Processes so as to provide data that is most informative about a parameter of in...