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ICML
2002
IEEE
16 years 1 months ago
Reinforcement Learning and Shaping: Encouraging Intended Behaviors
We explore dynamic shaping to integrate our prior beliefs of the final policy into a conventional reinforcement learning system. Shaping provides a positive or negative artificial...
Adam Laud, Gerald DeJong
106
Voted
ECAI
1994
Springer
15 years 4 months ago
Belief Revision in Multi-Agent Systems
The ability to respond sensibly to changing and conflicting beliefs is an integral part of intelligent agency. To this end, we outline the design and implementation of a Distribute...
Benedita Malheiro, Nicholas R. Jennings, Eugenio O...
107
Voted
GECCO
2009
Springer
150views Optimization» more  GECCO 2009»
15 years 7 months ago
Discrete dynamical genetic programming in XCS
A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks. This paper presents results fr...
Richard Preen, Larry Bull
84
Voted
NIPS
2007
15 years 1 months ago
Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning
Electrical power management in large-scale IT systems such as commercial datacenters is an application area of rapidly growing interest from both an economic and ecological perspe...
Gerald Tesauro, Rajarshi Das, Hoi Chan, Jeffrey O....
JMLR
2008
141views more  JMLR 2008»
15 years 15 days ago
Accelerated Neural Evolution through Cooperatively Coevolved Synapses
Many complex control problems require sophisticated solutions that are not amenable to traditional controller design. Not only is it difficult to model real world systems, but oft...
Faustino J. Gomez, Jürgen Schmidhuber, Risto ...