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» How to Dynamically Merge Markov Decision Processes
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AAAI
2006
14 years 11 months ago
Improving Approximate Value Iteration Using Memories and Predictive State Representations
Planning in partially-observable dynamical systems is a challenging problem, and recent developments in point-based techniques such as Perseus significantly improve performance as...
Michael R. James, Ton Wessling, Nikos A. Vlassis
GECCO
2005
Springer
152views Optimization» more  GECCO 2005»
15 years 3 months ago
GAMM: genetic algorithms with meta-models for vision
Recent adaptive image interpretation systems can reach optimal performance for a given domain via machine learning, without human intervention. The policies are learned over an ex...
Greg Lee, Vadim Bulitko
WISE
2002
Springer
15 years 2 months ago
An MDP-based Peer-to-Peer Search Server Network
A distributed search system consists of a large number of autonomous search servers logically connected in a peerto-peer network. Each search server maintains a local index of a c...
Yipeng Shen, Dik Lun Lee
ATAL
2004
Springer
15 years 3 months ago
Unifying Temporal and Structural Credit Assignment Problems
Single-agent reinforcement learners in time-extended domains and multi-agent systems share a common dilemma known as the credit assignment problem. Multi-agent systems have the st...
Adrian K. Agogino, Kagan Tumer
RTSS
2003
IEEE
15 years 2 months ago
Adaptive Coherency Maintenance Techniques for Time-Varying Data
Often, data used in on-line decision making (for example, in determining how to react to changes in process behavior, traffic flow control, etc.) is dynamic in nature and hence ...
Ratul kr. Majumdar, Kannan M. Moudgalya, Krithi Ra...