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NIPS
2008
15 years 1 months ago
Optimization on a Budget: A Reinforcement Learning Approach
Many popular optimization algorithms, like the Levenberg-Marquardt algorithm (LMA), use heuristic-based "controllers" that modulate the behavior of the optimizer during ...
Paul Ruvolo, Ian R. Fasel, Javier R. Movellan
NIPS
2004
15 years 1 months ago
Learning first-order Markov models for control
First-order Markov models have been successfully applied to many problems, for example in modeling sequential data using Markov chains, and modeling control problems using the Mar...
Pieter Abbeel, Andrew Y. Ng
CDC
2009
IEEE
138views Control Systems» more  CDC 2009»
14 years 9 months ago
Beyond local optimality: An improved approach to hybrid model learning
Abstract-- Local convergence is a limitation of many optimization approaches for multimodal functions. For hybrid model learning, this can mean a compromise in accuracy. We develop...
Stephanie Gil, Brian Williams
ATAL
2009
Springer
14 years 9 months ago
Replicator Dynamics for Multi-agent Learning: An Orthogonal Approach
Today's society is largely connected and many real life applications lend themselves to be modeled as multi-agent systems. Although such systems as well as their models are d...
Michael Kaisers, Karl Tuyls
TSMC
1998
78views more  TSMC 1998»
14 years 11 months ago
Automata learning and intelligent tertiary searching for stochastic point location
—Consider the problem of a robot (learning mechanism or algorithm) attempting to locate a point on a line. The mechanism interacts with a random environment which essentially inf...
B. John Oommen, Govindachari Raghunath