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NIPS
2001
13 years 11 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
ML
2000
ACM
150views Machine Learning» more  ML 2000»
13 years 10 months ago
Adaptive Retrieval Agents: Internalizing Local Context and Scaling up to the Web
This paper discusses a novel distributed adaptive algorithm and representation used to construct populations of adaptive Web agents. These InfoSpiders browse networked information ...
Filippo Menczer, Richard K. Belew
ICALT
2006
IEEE
14 years 4 months ago
Learner as a Designer of Digital Learning Tools
This paper will concentrate on how teacher can support learners in creating their own learning tools conducive to learning. Authors will discuss how the journey in creating differ...
Yasmin Bhattacharya, Madhumita Bhattacharya
JMLR
2006
118views more  JMLR 2006»
13 years 10 months ago
Learning Factor Graphs in Polynomial Time and Sample Complexity
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
Pieter Abbeel, Daphne Koller, Andrew Y. Ng
AAAI
2012
12 years 23 days ago
Model Learning and Real-Time Tracking Using Multi-Resolution Surfel Maps
For interaction with its environment, a robot is required to learn models of objects and to perceive these models in the livestreams from its sensors. In this paper, we propose a ...
Jörg Stückler, Sven Behnke