Distributed partially observable Markov decision problems (POMDPs) have emerged as a popular decision-theoretic approach for planning for multiagent teams, where it is imperative f...
Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs ...
This paper presents a search architecture that combines classical search techniques with spread activation techniques applied to a semantic model of a given domain. Given an ontol...
Cristiano Rocha, Daniel Schwabe, Marcus Poggi de A...
c Modular Abstractions for Linear Constraints David Monniaux VERIMAG June 27, 2008 se a method for automatically generating abstract transformers for static by abstract interpreta...
Current research in indexing and mining time series data has produced many interesting algorithms and representations. However, it has not led to algorithms that can scale to the ...