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» Learning Representation and Control in Continuous Markov Dec...
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ICML
2006
IEEE
14 years 3 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
14 years 2 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
12 years 9 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
13 years 10 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
13 years 11 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