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» Learning the required number of agents for complex tasks
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ATAL
2003
Springer
14 years 1 months ago
Towards a pareto-optimal solution in general-sum games
Multiagent learning literature has investigated iterated twoplayer games to develop mechanisms that allow agents to learn to converge on Nash Equilibrium strategy profiles. Such ...
Sandip Sen, Stéphane Airiau, Rajatish Mukhe...
ICML
2008
IEEE
14 years 8 months ago
Multi-task compressive sensing with Dirichlet process priors
Compressive sensing (CS) is an emerging field that, under appropriate conditions, can significantly reduce the number of measurements required for a given signal. In many applicat...
Yuting Qi, Dehong Liu, David B. Dunson, Lawrence C...
RSS
2007
135views Robotics» more  RSS 2007»
13 years 9 months ago
Learning omnidirectional path following using dimensionality reduction
Abstract— We consider the task of omnidirectional path following for a quadruped robot: moving a four-legged robot along any arbitrary path while turning in any arbitrary manner....
J. Zico Kolter, Andrew Y. Ng
ICDM
2010
IEEE
122views Data Mining» more  ICDM 2010»
13 years 5 months ago
Learning Preferences with Millions of Parameters by Enforcing Sparsity
We study the retrieval task that ranks a set of objects for a given query in the pairwise preference learning framework. Recently researchers found out that raw features (e.g. word...
Xi Chen, Bing Bai, Yanjun Qi, Qihang Lin, Jaime G....
AAAI
1996
13 years 9 months ago
Comet: An Application of Model-Based Reasoning to Accounting Systems
An important problem faced by auditors is gauging how much reliance can be placed on the accounting systems that process millions of transactions to produce the numbers summarized...
Robert Nado, Melanie Chams, Jeff Delisio, Walter H...