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ICMLA
2010
13 years 7 months ago
Multi-Agent Inverse Reinforcement Learning
Learning the reward function of an agent by observing its behavior is termed inverse reinforcement learning and has applications in learning from demonstration or apprenticeship l...
Sriraam Natarajan, Gautam Kunapuli, Kshitij Judah,...
MM
2005
ACM
134views Multimedia» more  MM 2005»
14 years 2 months ago
Formulating context-dependent similarity functions
Tasks of information retrieval depend on a good distance function for measuring similarity between data instances. The most effective distance function must be formulated in a con...
Gang Wu, Edward Y. Chang, Navneet Panda
TFS
2008
129views more  TFS 2008»
13 years 7 months ago
A Functional-Link-Based Neurofuzzy Network for Nonlinear System Control
Abstract--This study presents a functional-link-based neurofuzzy network (FLNFN) structure for nonlinear system control. The proposed FLNFN model uses a functional link neural netw...
Cheng-Hung Chen, Cheng-Jian Lin, Chin-Teng Lin
ICML
1998
IEEE
14 years 1 months ago
Learning to Drive a Bicycle Using Reinforcement Learning and Shaping
We present and solve a real-world problem of learning to drive a bicycle. We solve the problem by online reinforcement learning using the Sarsa(   )-algorithm. Then we solve the ...
Jette Randløv, Preben Alstrøm
CIKM
2006
Springer
14 years 1 months ago
A comparative study on classifying the functions of web page blocks
In this paper, we study the problem of learning block classification models to estimate block functions. We distinguish general models, which are learned across multiple sites, an...
Xiangye Xiao, Qiong Luo, Xing Xie, Wei-Ying Ma