This paper uses partially observable Markov decision processes (POMDP’s) as a basic framework for MultiAgent planning. We distinguish three perspectives: first one is that of a...
Bharaneedharan Rathnasabapathy, Piotr J. Gmytrasie...
Background: Existing hidden Markov model decoding algorithms do not focus on approximately identifying the sequence feature boundaries. Results: We give a set of algorithms to com...
Several centralized and distributed algorithms have been recently proposed to maximize the multicast lifetime for directional communications in wireless ad-hoc networks. Their per...
Abstract-- This paper introduces a deterministic approximation algorithm with error guarantees for computing the probability of propositional formulas over discrete random variable...
Approximate string matching problem is a common and often repeated task in information retrieval and bioinformatics. This paper proposes a generic design of a programmable array p...
Panagiotis D. Michailidis, Konstantinos G. Margari...