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» Compositional Models for Reinforcement Learning
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NIPS
2003
13 years 9 months ago
A Holistic Approach to Compositional Semantics: A Connectionist Model and Robot Experiments
We present a novel connectionist model for acquiring the semantics of a simple language through the behavioral experiences of a real robot. We focus on the “compositionality” ...
Yuuya Sugita, Jun Tani
BMCV
2000
Springer
14 years 2 days ago
Unsupervised Learning of Biologically Plausible Object Recognition Strategies
Recent psychological and neurological evidence suggests that biological object recognition is a process of matching sensed images to stored iconic memories. This paper presents a p...
Bruce A. Draper, Kyungim Baek
AIED
2009
Springer
14 years 2 months ago
Transfer Learning and Representation Discovery in Intelligent Tutoring Systems
We describe a novel framework developed for transfer learning within reinforcement learning (RL) problems. Then we exhibit how this framework can be extended to intelligent tutorin...
Kimberly Ferguson, Beverly Park Woolf, Sridhar Mah...
AAAI
2008
13 years 10 months ago
Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
Hirotaka Hachiya, Takayuki Akiyama, Masashi Sugiya...
JSW
2007
125views more  JSW 2007»
13 years 7 months ago
Description and Composition of E-Learning Services
— In this paper, we present our approach to describe and compose services for distant learning and research activities. For this purpose, we propose a metadata model for indexing...
Oussama Kassem Zein, Yvon Kermarrec