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ICCV
2003
IEEE
15 years 11 months ago
Tracking Articulated Body by Dynamic Markov Network
A new method for visual tracking of articulated objects is presented. Analyzing articulated motion is challenging because the dimensionality increase potentially demands tremendou...
Ying Wu, Gang Hua, Ting Yu
AAMAS
2007
Springer
15 years 3 months ago
Networks of Learning Automata and Limiting Games
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is that...
Peter Vrancx, Katja Verbeeck, Ann Nowé
ECAL
2007
Springer
15 years 1 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
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ICANN
2010
Springer
14 years 9 months ago
Multi-Dimensional Deep Memory Atari-Go Players for Parameter Exploring Policy Gradients
Abstract. Developing superior artificial board-game players is a widelystudied area of Artificial Intelligence. Among the most challenging games is the Asian game of Go, which, des...
Mandy Grüttner, Frank Sehnke, Tom Schaul, J&u...
CIG
2005
IEEE
15 years 3 months ago
Nannon: A Nano Backgammon for Machine Learning Research
A newly designed game is introduced, which feels like Backgammon, but has a simplified rule set. Unlike earlier attempts at simplifying the game, Nannon maintains enough features a...
Jordan B. Pollack