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» Learning the required number of agents for complex tasks
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GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
14 years 1 months ago
Co-evolving recurrent neurons learn deep memory POMDPs
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
Faustino J. Gomez, Jürgen Schmidhuber
ECAI
2004
Springer
14 years 1 months ago
Tractability Results for Automatic Contracting
Abstract. Automated negotiation techniques have received considerable attention over the past decade, and much progress has been made in developing negotiation protocols and strate...
Paul E. Dunne, Michael Laurence, Michael Wooldridg...
SPE
2002
105views more  SPE 2002»
13 years 7 months ago
Specifying a role-based guide for learning to work with an enterprise framework
Learning to work with enterprise frameworks requires considerable effort, because of the inherent complexity of all the knowledge that is needed. However, different roles in proje...
Wilhelm Hasselbring, Ralph van den Houdt
AI
2000
Springer
13 years 7 months ago
Wrapper induction: Efficiency and expressiveness
The Internet presents numerous sources of useful information--telephone directories, product catalogs, stock quotes, event listings, etc. Recently, many systems have been built th...
Nicholas Kushmerick
AAAI
2010
13 years 9 months ago
To Max or Not to Max: Online Learning for Speeding Up Optimal Planning
It is well known that there cannot be a single "best" heuristic for optimal planning in general. One way of overcoming this is by combining admissible heuristics (e.g. b...
Carmel Domshlak, Erez Karpas, Shaul Markovitch