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» Evolving neural network ensembles for control problems
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ACMACE
2006
ACM
14 years 1 months ago
Motivated reinforcement learning for non-player characters in persistent computer game worlds
Massively multiplayer online computer games are played in complex, persistent virtual worlds. Over time, the landscape of these worlds evolves and changes as players create and pe...
Kathryn Elizabeth Merrick, Mary Lou Maher
JMLR
2008
141views more  JMLR 2008»
13 years 7 months 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 ...
AAAI
1994
13 years 9 months ago
Parsing Embedded Clauses with Distributed Neural Networks
A distributed neural network model called SPEC for processing sentences with recursive relative clauses is described. The model is based on separating the tasks of segmenting the ...
Risto Miikkulainen, Dennis Bijwaard
SIGMETRICS
2005
ACM
163views Hardware» more  SIGMETRICS 2005»
14 years 1 months ago
Smooth switching problem in buffered crossbar switches
Scalability considerations drive the switch fabric design to evolve from output queueing to input queueing and further to combined input and crosspoint queueing (CICQ). However, f...
Simin He, Shutao Sun, Wei Zhao, Yanfeng Zheng, Wen...
GECCO
2009
Springer
14 years 9 days ago
NEAT in increasingly non-linear control situations
Evolution of neural networks, as implemented in NEAT, has proven itself successful on a variety of low-level control problems such as pole balancing and vehicle control. Nonethele...
Matthias J. Linhardt, Martin V. Butz