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AISC
2004
Springer
16 years 1 days ago
New Developments in Symmetry Breaking in Search Using Computational Group Theory
Symmetry-breaking in constraint satisfaction problems (CSPs) is a well-established area of AI research which has recently developed strong interactions with symbolic computation, i...
Tom Kelsey, Steve Linton, Colva M. Roney-Dougal
GECCO
2004
Springer
16 years 16 hour ago
Distributed Constraint Satisfaction, Restricted Recombination, and Hybrid Genetic Search
In this paper, we present simple and genetic forms of an evolutionary paradigm known as a society of hill-climbers (SoHC). We compare these simple and genetic SoHCs on a test suite...
Gerry V. Dozier, Hurley Cunningham, Winard Britt, ...
AAAI
2007
15 years 9 months ago
Temporal Difference and Policy Search Methods for Reinforcement Learning: An Empirical Comparison
Reinforcement learning (RL) methods have become popular in recent years because of their ability to solve complex tasks with minimal feedback. Both genetic algorithms (GAs) and te...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
ECAI
2006
Springer
15 years 8 months ago
Calibrating Probability Density Forecasts with Multi-Objective Search
Abstract. In this paper, we show that the optimization of density forecasting models for regression in machine learning can be formulated as a multi-objective problem. We describe ...
Michael Carney, Padraig Cunningham
CP
2008
Springer
15 years 8 months ago
Guiding Search in QCSP+ with Back-Propagation
The Quantified Constraint Satisfaction Problem (QCSP) has been introduced to express situations in which we are not able to control the value of some of the variables (the universa...
Guillaume Verger, Christian Bessiere