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GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
15 years 4 months ago
Co-evolving recurrent neurons learn deep memory POMDPs
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
Faustino J. Gomez, Jürgen Schmidhuber
GECCO
2005
Springer
116views Optimization» more  GECCO 2005»
15 years 4 months ago
Measuring, enabling and comparing modularity, regularity and hierarchy in evolutionary design
For computer-automated design systems to scale to complex designs they must be able to produce designs that exhibit the characteristics of modularity, regularity and hierarchy –...
Gregory Hornby
ICCBR
2005
Springer
15 years 4 months ago
Learning to Win: Case-Based Plan Selection in a Real-Time Strategy Game
While several researchers have applied case-based reasoning techniques to games, only Ponsen and Spronck (2004) have addressed the challenging problem of learning to win real-time ...
David W. Aha, Matthew Molineaux, Marc J. V. Ponsen
ICES
2005
Springer
176views Hardware» more  ICES 2005»
15 years 4 months ago
Consensus-Based Evaluation for Fault Isolation and On-line Evolutionary Regeneration
While the fault repair capability of Evolvable Hardware (EH) approaches have been previously demonstrated, further improvements to fault handling capability can be achieved by exp...
Kening Zhang, Ronald F. DeMara, Carthik A. Sharma
NIME
2005
Springer
136views Music» more  NIME 2005»
15 years 4 months ago
Learning Advanced Skills on New Instruments (or practising scales and arpeggios on your NIME)
When learning a classical instrument, people often either take lessons in which an existing body of “technique” is delivered, evolved over generations of performers, or in som...
Sageev Oore