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» Compositional Models for Reinforcement Learning
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ECAL
2007
Springer
13 years 11 months ago
Genotype Reuse More Important than Genotype Size in Evolvability of Embodied Neural Networks
odel of Embodiment on Abstract Systems: from Hierarchy to Heterarchy Kohei Nakajima, Soya Shinkai, Takashi Ikegami A Behavior-Based Model of the Hydra, Phylum Cnidaria Malin Aktius...
Chad W. Seys, Randall D. Beer
GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
13 years 11 months ago
Indirect co-evolution for understanding belief in an incomplete information dynamic game
This study aims to design a new co-evolution algorithm, Mixture Co-evolution which enables modeling of integration and composition of direct co-evolution and indirect coevolution....
Nanlin Jin
GREC
2003
Springer
14 years 1 months ago
User Adaptation for Online Sketchy Shape Recognition
This paper presents a method of online sketchy shape recognition that can adapt to different user sketching styles. The adaptation principle is based on incremental active learning...
Zhengxing Sun, Liu Wenyin, Binbin Peng, Bin Zhang,...
ARCS
2005
Springer
14 years 1 months ago
Adaptive Object Acquisition
We propose an active vision system for object acquisition. The core of our approach is a reinforcement learning module which learns a strategy to scan an object. The agent moves a...
Gabriele Peters, Claus-Peter Alberts, Markus Bries...
ATAL
2006
Springer
13 years 11 months ago
Convergence analysis for collective vocabulary development
We study how decentralized agents can develop a shared vocabulary without global coordination. Answering this question can help us understand the emergence of many communication s...
Jun Wang, Les Gasser, Jim Houk