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» Learning Representation and Control in Continuous Markov Dec...
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ICML
2006
IEEE
16 years 1 months ago
Automatic basis function construction for approximate dynamic programming and reinforcement learning
We address the problem of automatically constructing basis functions for linear approximation of the value function of a Markov Decision Process (MDP). Our work builds on results ...
Philipp W. Keller, Shie Mannor, Doina Precup
ATAL
2005
Springer
16 years 1 months ago
Modeling task allocation using a decision theoretic model
Mediation is the process of decomposing a task into subtasks, finding agents suitable for these subtasks and negotiating with agents to obtain commitments to execute these subtas...
Sherief Abdallah, Victor R. Lesser
AAAI
2011
14 years 7 months ago
An Online Spectral Learning Algorithm for Partially Observable Nonlinear Dynamical Systems
Recently, a number of researchers have proposed spectral algorithms for learning models of dynamical systems—for example, Hidden Markov Models (HMMs), Partially Observable Marko...
Byron Boots, Geoffrey J. Gordon
AAAI
1994
15 years 8 months ago
Control Strategies for a Stochastic Planner
We present new algorithms for local planning over Markov decision processes. The base-level algorithm possesses several interesting features for control of computation, based on s...
Jonathan Tash, Stuart J. Russell
AAAI
2007
15 years 9 months ago
Continuous State POMDPs for Object Manipulation Tasks
My research focus is on using continuous state partially observable Markov decision processes (POMDPs) to perform object manipulation tasks using a robotic arm. During object mani...
Emma Brunskill