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AAAI
2006
13 years 10 months ago
On the Difficulty of Modular Reinforcement Learning for Real-World Partial Programming
In recent years there has been a great deal of interest in "modular reinforcement learning" (MRL). Typically, problems are decomposed into concurrent subgoals, allowing ...
Sooraj Bhat, Charles Lee Isbell Jr., Michael Matea...
SODA
2003
ACM
142views Algorithms» more  SODA 2003»
13 years 10 months ago
The similarity metric
—A new class of distances appropriate for measuring similarity relations between sequences, say one type of similarity per distance, is studied. We propose a new “normalized in...
Ming Li, Xin Chen, Xin Li, Bin Ma, Paul M. B. Vit&...
ATAL
2010
Springer
13 years 10 months ago
Risk-sensitive planning in partially observable environments
Partially Observable Markov Decision Process (POMDP) is a popular framework for planning under uncertainty in partially observable domains. Yet, the POMDP model is riskneutral in ...
Janusz Marecki, Pradeep Varakantham
DEDS
2007
104views more  DEDS 2007»
13 years 9 months ago
Trellis Processes : A Compact Representation for Runs of Concurrent Systems
The unfolding of a concurrent system represents in a compact manner all possible runs of this system. Unfoldings are used in many applications, ranging from model-checking (offlin...
Eric Fabre
JMLR
2006
103views more  JMLR 2006»
13 years 9 months ago
Pattern Recognition for Conditionally Independent Data
In this work we consider the task of relaxing the i.i.d. assumption in pattern recognition (or classification), aiming to make existing learning algorithms applicable to a wider r...
Daniil Ryabko