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ICANN
2001
Springer
15 years 4 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
15 years 1 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
15 years 1 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
96
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CDC
2008
IEEE
169views Control Systems» more  CDC 2008»
15 years 2 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»
14 years 11 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