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» Can Doxastic Agents Learn
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ATAL
2008
Springer
15 years 2 months ago
Graph Laplacian based transfer learning in reinforcement learning
The aim of transfer learning is to accelerate learning in related domains. In reinforcement learning, many different features such as a value function and a policy can be transfer...
Yi-Ting Tsao, Ke-Ting Xiao, Von-Wun Soo
82
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ICML
1989
IEEE
15 years 4 months ago
Uncertainty Based Selection of Learning Experiences
The training experiences needed by a learning system may be selected by either an external agent or the system itself. We show that knowledge of the current state of the learner&#...
Paul D. Scott, Shaul Markovitch
AAAI
2007
15 years 3 months ago
Autonomous Development of a Grounded Object Ontology by a Learning Robot
We describe how a physical robot can learn about objects from its own autonomous experience in the continuous world. The robot identifies statistical regularities that allow it t...
Joseph Modayil, Benjamin Kuipers
NIPS
2000
15 years 2 months ago
Balancing Multiple Sources of Reward in Reinforcement Learning
For many problems which would be natural for reinforcement learning, the reward signal is not a single scalar value but has multiple scalar components. Examples of such problems i...
Christian R. Shelton
JAIR
2007
127views more  JAIR 2007»
15 years 19 days ago
Learning Symbolic Models of Stochastic Domains
In this article, we work towards the goal of developing agents that can learn to act in complex worlds. We develop a a new probabilistic planning rule representation to compactly ...
Hanna M. Pasula, Luke S. Zettlemoyer, Leslie Pack ...