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WSC
2000
14 years 11 months ago
Using simulation and critical points to define states in continuous search spaces
Many artificial intelligence techniques rely on the notion ate" as an abstraction of the actual state of the nd an "operator" as an abstraction of the actions that ...
Marc S. Atkin, Paul R. Cohen
NIPS
1990
14 years 10 months ago
Bumptrees for Efficient Function, Constraint and Classification Learning
A new class of data structures called "bumptrees" is described. These structures are useful for efficiently implementing a number of neural network related operations. A...
Stephen M. Omohundro
ATAL
2010
Springer
14 years 10 months ago
A decentralised coordination algorithm for minimising conflict and maximising coverage in sensor networks
In large wireless sensor networks, the problem of assigning radio frequencies to sensing agents such that no two connected sensors are assigned the same value (and will thus inter...
Ruben Stranders, Alex Rogers, Nicholas R. Jennings
95
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ATAL
2010
Springer
14 years 10 months ago
Closing the learning-planning loop with predictive state representations
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon
ATAL
2010
Springer
14 years 10 months ago
Frequency adjusted multi-agent Q-learning
Multi-agent learning is a crucial method to control or find solutions for systems, in which more than one entity needs to be adaptive. In today's interconnected world, such s...
Michael Kaisers, Karl Tuyls
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