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NN
2007
Springer
105views Neural Networks» more  NN 2007»
13 years 7 months ago
Guiding exploration by pre-existing knowledge without modifying reward
Reinforcement learning is based on exploration of the environment and receiving reward that indicates which actions taken by the agent are good and which ones are bad. In many app...
Kary Främling
ICANN
2003
Springer
14 years 26 days ago
Learning Rule Representations from Boolean Data
We discuss a Probably Approximate Correct (PAC) learning paradigm for Boolean formulas, which we call PAC meditation, where the class of formulas to be learnt is not known in advan...
Bruno Apolloni, Andrea Brega, Dario Malchiodi, Gio...
IJCAI
2003
13 years 9 months ago
A Learning Algorithm for Localizing People Based on Wireless Signal Strength that Uses Labeled and Unlabeled Data
This paper summarizes a probabilistic approach for localizing people through the signal strengths of a wireless IEEE 802.11b network. Our approach uses data labeled by ground trut...
Sebastian Thrun, Geoffrey J. Gordon, Frank Pfennin...
AIPS
1994
13 years 9 months ago
Robot Motion Planning Integrating Planning Strategies and Learning Methods
Robot motion planning in a dynamic cluttered workspace requires the capability of dealing with obstacles and deadlock situations. The paper analyzes situations where the robot is ...
Luca Maria Gambardella, Cristina Versino
AAAI
2007
13 years 10 months ago
A Connectionist Cognitive Model for Temporal Synchronisation and Learning
The importance of the efforts towards integrating the symbolic and connectionist paradigms of artificial intelligence has been widely recognised. Integration may lead to more e...
Luís C. Lamb, Rafael V. Borges, Artur S. d'...