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GECCO
2009
Springer
204views Optimization» more  GECCO 2009»
14 years 1 months ago
Combined structure and motion extraction from visual data using evolutionary active learning
We present a novel stereo vision modeling framework that generates approximate, yet physically-plausible representations of objects rather than creating accurate models that are c...
Krishnanand N. Kaipa, Josh C. Bongard, Andrew N. M...
PG
1999
IEEE
14 years 1 months ago
Mesh Approximation Using a Volume-Based Metric
In this paper we introduce a mesh approximation method that uses a volume-based metric. After a geometric simplification, we minimize the volume between the simplified mesh and th...
Pierre Alliez, Nathalie Laurent, Henri Sanson, Fra...
ARTMED
2002
121views more  ARTMED 2002»
13 years 8 months ago
An evolutionary artificial neural networks approach for breast cancer diagnosis
This paper presents an evolutionary artificial neural network approach based on the pareto differential evolution algorithm augmented with local search for the prediction of breas...
Hussein A. Abbass
SEAL
1998
Springer
14 years 1 months ago
Evolutionary Programming-Based Uni-vector Field Method for Fast Mobile Robot Navigation
Most of the obstacle avoidance techniques do not consider the robot orientation or its nal angle at the target position. These techniques deal with the robot position only and are ...
Yong-Jae Kim, Dong-Han Kim, Jong-Hwan Kim
PKDD
2009
Springer
144views Data Mining» more  PKDD 2009»
14 years 3 months ago
Compositional Models for Reinforcement Learning
Abstract. Innovations such as optimistic exploration, function approximation, and hierarchical decomposition have helped scale reinforcement learning to more complex environments, ...
Nicholas K. Jong, Peter Stone