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» Reinforcement Learning: Past, Present and Future
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JIKM
2006
167views more  JIKM 2006»
13 years 7 months ago
Learning Trajectory Information with Neural Networks and the Markov Model to Develop Intelligent Location-Based Services
In the development of location-based services, various location-sensing techniques and experimental/commercial services have been used. However, conventional location-based service...
Sang-Jun Han, Sung-Bae Cho
SGAI
2010
Springer
13 years 5 months ago
Hierarchical Traces for Reduced NSM Memory Requirements
This paper presents work on using hierarchical long term memory to reduce the memory requirements of nearest sequence memory (NSM) learning, a previously published, instance-based ...
Torbjørn S. Dahl
CEEMAS
2005
Springer
14 years 28 days ago
A Direct Reputation Model for VO Formation
We show that reputation is a basic ingredient in the Virtual Organisation (VO) formation process. Agents can use their experiences gained in direct past interactions to model other...
Arturo Avila-Rosas, Michael Luck
AIPS
2006
13 years 8 months ago
Reusing and Building a Policy Library
Policy Reuse is a method to improve reinforcement learning with the ability to solve multiple tasks by building upon past problem solving experience, as accumulated in a Policy Li...
Fernando Fernández, Manuela M. Veloso
SIGCSE
2008
ACM
116views Education» more  SIGCSE 2008»
13 years 7 months ago
Evaluating a breadth-first cs 1 for scientists
This paper presents a thorough evaluation of CS for Scientists, a CS 1 course designed to provide future scientists with an overview of the discipline. The course takes a breadth-...
Zachary Dodds, Ran Libeskind-Hadas, Christine Alva...