5302 search results - page 370 / 1061 » Learning How to Separate |
194
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ICML
2005
IEEE
16 years 7 months ago
2005
IEEE
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. In this pap...
191
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ICML
2003
IEEE
16 years 7 months ago
2003
IEEE
Learning in many multi-agent settings is inherently repeated play. This calls into question the naive application of single play Nash equilibria in multi-agent learning and sugges...
161
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ICML
2003
IEEE
16 years 7 months ago
2003
IEEE
An important issue in reinforcement learning is how to incorporate expert knowledge in a principled manner, especially as we scale up to real-world tasks. In this paper, we presen...
192
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ALT
2005
Springer
16 years 3 months ago
2005
Springer
This paper shows how universal learning can be achieved with expert advice. To this aim, we specify an experts algorithm with the following characteristics: (a) it uses only feedba...
171
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MICAI
2009
Springer
16 years 1 months ago
2009
Springer
Reinforcement Learning is a commonly used technique in robotics, however, traditional algorithms are unable to handle large amounts of data coming from the robot’s sensors, requi...