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PDPTA
2003
13 years 8 months ago
Java Resources for Teaching Reinforcement Learning
— In this paper we present a library of classes for programming reinforcement learning simulations in Java. This library is based upon the standard by Sutton and Santamaria [1], ...
Amy J. Kerr, Todd W. Neller, Christopher J. La Pil...
IEEEPACT
2008
IEEE
14 years 1 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...
ICML
1999
IEEE
14 years 7 months ago
Implicit Imitation in Multiagent Reinforcement Learning
Imitation is actively being studied as an effective means of learning in multi-agent environments. It allows an agent to learn how to act well (perhaps optimally) by passively obs...
Bob Price, Craig Boutilier
ICML
2004
IEEE
14 years 7 months ago
Adaptive cognitive orthotics: combining reinforcement learning and constraint-based temporal reasoning
Reminder systems support people with impaired prospective memory and/or executive function, by providing them with reminders of their functional daily activities. We integrate tem...
Matthew R. Rudary, Satinder P. Singh, Martha E. Po...
GECCO
2005
Springer
153views Optimization» more  GECCO 2005»
14 years 16 days ago
Evolving neural network ensembles for control problems
In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...
David Pardoe, Michael S. Ryoo, Risto Miikkulainen