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» Metaphor for learning: an evolutionary algorithm
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EC
2008
146views ECommerce» more  EC 2008»
13 years 7 months ago
Automated Discovery of Local Search Heuristics for Satisfiability Testing
The development of successful metaheuristic algorithms such as local search for a difficult problems such as satisfiability testing (SAT) is a challenging task. We investigate an ...
Alex S. Fukunaga
AAMAS
2007
Springer
14 years 1 months ago
Bifurcation Analysis of Reinforcement Learning Agents in the Selten's Horse Game
Abstract. The application of reinforcement learning algorithms to multiagent domains may cause complex non-convergent dynamics. The replicator dynamics, commonly used in evolutiona...
Alessandro Lazaric, Jose Enrique Munoz de Cote, Fa...
AGI
2008
13 years 9 months ago
An Integrative Methodology for Teaching Embodied Non-Linguistic Agents, Applied to Virtual Animals in Second Life
A teaching methodology called Imitative-Reinforcement-Corrective (IRC) learning is described, and proposed as a general approach for teaching embodied non-linguistic AGI systems. I...
Ben Goertzel, Cassio Pennachin, Nil Geisweiller, M...
CP
2005
Springer
13 years 9 months ago
Evolving Variable-Ordering Heuristics for Constrained Optimisation
In this paper we present and evaluate an evolutionary approach for learning new constraint satisfaction algorithms, specifically for MAX-SAT optimisation problems. Our approach of...
Stuart Bain, John Thornton, Abdul Sattar
GECCO
2009
Springer
188views Optimization» more  GECCO 2009»
13 years 11 months ago
Exploiting multiple classifier types with active learning
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
Zhenyu Lu, Josh Bongard