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» Algorithms for Inverse Reinforcement Learning
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ATAL
2008
Springer
14 years 11 months ago
Adaptive Kanerva-based function approximation for multi-agent systems
In this paper, we show how adaptive prototype optimization can be used to improve the performance of function approximation based on Kanerva Coding when solving largescale instanc...
Cheng Wu, Waleed Meleis
83
Voted
WWW
2010
ACM
15 years 4 months ago
iRIN: image retrieval in image-rich information networks
In this demo, we present a system called iRIN designed for performing image retrieval in image-rich information networks. We first introduce MoK-SimRank to significantly improve...
Xin Jin, Jiebo Luo, Jie Yu, Gang Wang, Dhiraj Josh...
103
Voted
ATAL
2006
Springer
15 years 1 months ago
Learning to cooperate in multi-agent social dilemmas
In many Multi-Agent Systems (MAS), agents (even if selfinterested) need to cooperate in order to maximize their own utilities. Most of the multi-agent learning algorithms focus on...
Jose Enrique Munoz de Cote, Alessandro Lazaric, Ma...
85
Voted
ICML
2008
IEEE
15 years 10 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...
75
Voted
EDUTAINMENT
2006
Springer
15 years 1 months ago
Generating 3D Paper-Cutting Effects
In this paper we describe a framework for generating 3D paper-cutting effects on mesh models. The framework involves the construction of model defined paper-cutting patterns, extr...
Yan Li, Jinhui Yu, Honxin Zhang, Jiaoying Shi