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...
—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&...
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 ...
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...
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...