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ICML
2006
IEEE
14 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
ICVS
2001
Springer
14 years 7 days ago
Adapting Object Recognition across Domains: A Demonstration
High-level vision systems use object, scene or domain specific knowledge to interpret images. Unfortunately, this knowledge has to be acquired for every domain. This makes it diffi...
Bruce A. Draper, Ulrike Ahlrichs, Dietrich Paulus
AAAI
2007
13 years 10 months ago
Situated Conversational Agents
A Situated Conversational Agent (SCA) is an agent that engages in dialog about the context within which it is embedded. Situated dialog is characterized by its deep connection to ...
William Thompson
IJCAI
2007
13 years 9 months ago
A Hybridized Planner for Stochastic Domains
Markov Decision Processes are a powerful framework for planning under uncertainty, but current algorithms have difficulties scaling to large problems. We present a novel probabil...
Mausam, Piergiorgio Bertoli, Daniel S. Weld
FLAIRS
2001
13 years 9 months ago
Probabilistic Planning for Behavior-Based Robots
Partially Observable Markov Decision Process models (POMDPs) have been applied to low-level robot control. We show how to use POMDPs differently, namely for sensorplanning in the ...
Amin Atrash, Sven Koenig