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ICANN
2001
Springer
14 years 2 months ago
Market-Based Reinforcement Learning in Partially Observable Worlds
Unlike traditional reinforcement learning (RL), market-based RL is in principle applicable to worlds described by partially observable Markov Decision Processes (POMDPs), where an ...
Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber
AAAI
2004
13 years 11 months ago
Generating Safe Assumption-Based Plans for Partially Observable, Nondeterministic Domains
Reactive planning using assumptions is a well-known approach to tackle complex planning problems for nondeterministic, partially observable domains. However, assumptions may be wr...
Alexandre Albore, Piergiorgio Bertoli
AAAI
2006
13 years 11 months ago
Learning Partially Observable Action Models: Efficient Algorithms
We present tractable, exact algorithms for learning actions' effects and preconditions in partially observable domains. Our algorithms maintain a propositional logical repres...
Dafna Shahaf, Allen Chang, Eyal Amir
CDC
2008
IEEE
169views Control Systems» more  CDC 2008»
13 years 11 months ago
Control of underactuated mechanical systems: Observer design and position feedback stabilization
We identify a class of mechanical systems for which a globally exponentially stable reduced order observer can be designed. The class is characterized by (the solvability of) a set...
Aneesh Venkatraman, Romeo Ortega, Ioannis Sarras, ...
PAMI
2007
186views more  PAMI 2007»
13 years 9 months ago
Value-Directed Human Behavior Analysis from Video Using Partially Observable Markov Decision Processes
—This paper presents a method for learning decision theoretic models of human behaviors from video data. Our system learns relationships between the movements of a person, the co...
Jesse Hoey, James J. Little