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GECCO
2008
Springer
155views Optimization» more  GECCO 2008»
13 years 10 months ago
Towards memoryless model building
Probabilistic model building methods can render difficult problems feasible by identifying and exploiting dependencies. They build a probabilistic model from the statistical prope...
David Iclanzan, Dumitru Dumitrescu
ASC
2010
13 years 9 months ago
Simplifying Particle Swarm Optimization
The general purpose optimization method known as Particle Swarm Optimization (PSO) has received much attention in past years, with many attempts to find the variant that performs ...
M. E. H. Pedersen, Andrew J. Chipperfield
AR
2007
105views more  AR 2007»
13 years 9 months ago
Reinforcement learning of a continuous motor sequence with hidden states
—Reinforcement learning is the scheme for unsupervised learning in which robots are expected to acquire behavior skills through self-explorations based on reward signals. There a...
Hiroaki Arie, Tetsuya Ogata, Jun Tani, Shigeki Sug...
AR
2007
99views more  AR 2007»
13 years 9 months ago
Experience-based imitation using RNNPB
Abstract— Robot imitation is a useful and promising alternative to robot programming. Robot imitation involves two crucial issues. The first is how a robot can imitate a human w...
Ryunosuke Yokoya, Tetsuya Ogata, Jun Tani, Kazunor...
BC
2007
107views more  BC 2007»
13 years 9 months ago
Decoding spike train ensembles: tracking a moving stimulus
We consider the issue of how to read out the information from nonstationary spike train ensembles. Based on the theory of censored data in statistics, we propose a ‘censored’ m...
Enrico Rossoni, Jianfeng Feng