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IROS
2007
IEEE
132views Robotics» more  IROS 2007»
14 years 2 months ago
Hysteretic q-learning : an algorithm for decentralized reinforcement learning in cooperative multi-agent teams
— Multi-agent systems (MAS) are a field of study of growing interest in a variety of domains such as robotics or distributed controls. The article focuses on decentralized reinf...
Laëtitia Matignon, Guillaume J. Laurent, Nadi...
CVPR
2010
IEEE
14 years 4 months ago
Learning Full Pairwise Affinities for Spectral Segmentation
This paper studies the problem of learning a full range of pairwise affinities gained by integrating local grouping cues for spectral segmentation. The overall quality of the spect...
Tae Hoon Kim (Seoul National University), Kyoung M...
CDC
2009
IEEE
159views Control Systems» more  CDC 2009»
14 years 13 days ago
A distributed machine learning framework
Abstract— A distributed online learning framework for support vector machines (SVMs) is presented and analyzed. First, the generic binary classification problem is decomposed in...
Tansu Alpcan, Christian Bauckhage
ACMIDC
2008
13 years 9 months ago
Playing with the sound maker: do embodied metaphors help children learn?
In this paper we present the results of a comparative study that explores the potential benefits of using embodied ion to help children, aged 7 to 10, learn abstract concepts rela...
Alissa Nicole Antle, Milena Droumeva, Greg Corness
CORR
2010
Springer
105views Education» more  CORR 2010»
13 years 6 months ago
Optimism in Reinforcement Learning Based on Kullback-Leibler Divergence
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
Sarah Filippi, Olivier Cappé, Aurelien Gari...