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ICML
1994
IEEE
14 years 1 months ago
Learning Without State-Estimation in Partially Observable Markovian Decision Processes
Reinforcement learning (RL) algorithms provide a sound theoretical basis for building learning control architectures for embedded agents. Unfortunately all of the theory and much ...
Satinder P. Singh, Tommi Jaakkola, Michael I. Jord...
AAAI
2006
13 years 11 months ago
Learning Partially Observable Action Schemas
We present an algorithm that derives actions' effects and preconditions in partially observable, relational domains. Our algorithm has two unique features: an expressive rela...
Dafna Shahaf, Eyal Amir
ANOR
2010
85views more  ANOR 2010»
13 years 10 months ago
Inventory management with partially observed nonstationary demand
Abstract. We consider a continuous-time model for inventory management with Markov modulated non-stationary demands. We introduce active learning by assuming that the state of the ...
Erhan Bayraktar, Michael Ludkovski
JAIR
2008
148views more  JAIR 2008»
13 years 9 months ago
Learning Partially Observable Deterministic Action Models
We present exact algorithms for identifying deterministic-actions' effects and preconditions in dynamic partially observable domains. They apply when one does not know the ac...
Eyal Amir, Allen Chang
FC
2010
Springer
226views Cryptology» more  FC 2010»
14 years 1 months ago
Shoulder-Surfing Safe Login in a Partially Observable Attacker Model
Abstract. Secure login methods based on human cognitive skills can be classified into two categories based on information available to a passive attacker: (i) the attacker fully ob...
Toni Perkovic, Mario Cagalj, Nitesh Saxena