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148
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NIPS
2004
15 years 8 months ago
Intrinsically Motivated Reinforcement Learning
Psychologists call behavior intrinsically motivated when it is engaged in for its own sake rather than as a step toward solving a specific problem of clear practical value. But wh...
Satinder P. Singh, Andrew G. Barto, Nuttapong Chen...
209
Voted
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
16 years 7 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
ECTEL
2007
Springer
16 years 1 months ago
Adaptation of the ACO Heuristic for Sequencing Learning Activities
This paper describes an initiative aimed at adapting swarm intelligence techniques (in particular, Ant Colony Optimization) to an e-learning environment, thanks to the fact that th...
Sergio Gutiérrez Santos, Grégory Val...
IPOM
2007
Springer
16 years 1 months ago
Cognitive Network Management with Reinforcement Learning for Wireless Mesh Networks
We present a framework of cognitive network management by means of an autonomic reconfiguration scheme. We propose a network architecture that enables intelligent services to meet ...
Minsoo Lee, Dan Marconett, Xiaohui Ye, S. J. Ben Y...
178
Voted
EWCBR
2008
Springer
15 years 8 months ago
Recognizing the Enemy: Combining Reinforcement Learning with Strategy Selection Using Case-Based Reasoning
This paper presents CBRetaliate, an agent that combines Case-Based Reasoning (CBR) and Reinforcement Learning (RL) algorithms. Unlike most previous work where RL is used to improve...
Bryan Auslander, Stephen Lee-Urban, Chad Hogg, H&e...