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IEEEPACT
2008
IEEE
13 years 11 months ago
Feature selection and policy optimization for distributed instruction placement using reinforcement learning
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...
AAAI
2010
13 years 6 months ago
Bayesian Policy Search for Multi-Agent Role Discovery
Bayesian inference is an appealing approach for leveraging prior knowledge in reinforcement learning (RL). In this paper we describe an algorithm for discovering different classes...
Aaron Wilson, Alan Fern, Prasad Tadepalli
ICML
2002
IEEE
14 years 5 months ago
Hierarchically Optimal Average Reward Reinforcement Learning
Two notions of optimality have been explored in previous work on hierarchical reinforcement learning (HRL): hierarchical optimality, or the optimal policy in the space defined by ...
Mohammad Ghavamzadeh, Sridhar Mahadevan
IAT
2007
IEEE
13 years 11 months ago
Noise Tolerance in Reinforcement Learning Algorithms
This paper proposes a mechanism of noise tolerance for reinforcement learning algorithms. An adaptive agent that employs reinforcement learning algorithms may receive and accumula...
Richardson Ribeiro, Alessandro L. Koerich, Fabr&ia...
NIPS
2001
13 years 6 months ago
Switch Packet Arbitration via Queue-Learning
In packet switches, packets queue at switch inputs and contend for outputs. The contention arbitration policy directly affects switch performance. The best policy depends on the c...
Timothy X. Brown