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ACL
1998
13 years 11 months ago
Experiments with Learning Parsing Heuristics
Any large language processing software relies in its operation on heuristic decisions concerning the strategy of processing. These decisions are usually "hard-wired" int...
Sylvain Delisle, Sylvain Létourneau, Stan M...
ICANN
2009
Springer
14 years 2 months ago
Constrained Learning Vector Quantization or Relaxed k-Separability
Neural networks and other sophisticated machine learning algorithms frequently miss simple solutions that can be discovered by a more constrained learning methods. Transition from ...
Marek Grochowski, Wlodzislaw Duch
TSMC
2008
146views more  TSMC 2008»
13 years 10 months ago
Decentralized Learning in Markov Games
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is tha...
Peter Vrancx, Katja Verbeeck, Ann Nowé
ECAI
2004
Springer
14 years 3 months ago
Avatars That Learn How to Behave
It is possible to model avatars that learn to simulate object manipulations and other complex actions. A number of applications may benefit from this technique including safety, e...
Adam Szarowicz, Paolo Remagnino
AAAI
1997
13 years 11 months ago
Benefits of Learning in Negotiation
Negotiation has been extensively discussed in gametheoretic, economic, and management science literatures for decades. Recent growing interest in electronic commerce has given inc...
Dajun Zeng, Katia P. Sycara