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» Intrinsically Motivated Reinforcement Learning
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CACM
2010
105views more  CACM 2010»
13 years 8 months ago
Censored exploration and the dark pool problem
We introduce and analyze a natural algorithm for multi-venue exploration from censored data, which is motivated by the Dark Pool Problem of modern quantitative finance. We prove t...
Kuzman Ganchev, Yuriy Nevmyvaka, Michael Kearns, J...
CDC
2010
IEEE
160views Control Systems» more  CDC 2010»
13 years 2 months ago
Adaptive bases for Q-learning
Abstract-- We consider reinforcement learning, and in particular, the Q-learning algorithm in large state and action spaces. In order to cope with the size of the spaces, a functio...
Dotan Di Castro, Shie Mannor
LWA
2007
13 years 9 months ago
Towards Learning User-Adaptive State Models in a Conversational Recommender System
Typical conversational recommender systems support interactive strategies that are hard-coded in advance and followed rigidly during a recommendation session. In fact, Reinforceme...
Tariq Mahmood, Francesco Ricci
NIPS
2001
13 years 9 months ago
Model-Free Least-Squares Policy Iteration
We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
Michail G. Lagoudakis, Ronald Parr
HCI
2007
13 years 9 months ago
Immersive Digital Games: The Interfaces for Next-Generation E-Learning?
The intrinsic motivation to play, and therefore to learn, that might be provided by digital educational games teases researchers and developers. However, existing educational games...
Michael D. Kickmeier-Rust, Neil Peirce, Owen Conla...