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A Bayesian Network Approach to Control of Networked Markov Decision Processes
Decision Processes Contro
2015/6/19
We consider the problem of finding an optimal feedback controller for a networked Markov decision process. Specifically, we consider a network of interconnected subsystems, where each subsystem evolve...
Information State for Markov Decision Processes with Network Delays
Network Delays Decision Processes
2015/6/19
We consider a networked control system, where each subsystem evolves as a Markov decision process (MDP). Each subsystem is coupled to its neighbors via communication links over which the signals are d...
A Dynamic Programming Algorithm for Decentralized Markov Decision Processes with a Broadcast Structure
Decentralized Markov Decision Algorithm
2015/6/19
We give an optimal dynamic programming algorithm to solve a class of finite-horizon decentralized Markov decision processes (MDPs). We consider problems with a broadcast information structure that con...
Optimal Control of Distributed Markov Decision Processes with Network Delays
Network Delays Decision Processes
2015/6/19
We consider the problem of finding an optimal feedback controller for a network of interconnected subsystems, each of which is a Markov decision process. Each subsystem is coupled to its neighbors via...
We consider a networked control system, where each subsystem evolves as a Markov decision process with some extra inputs from other systems. Each subsystem is coupled to its neighbors via communicatio...
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...