In this paper, we build on previous work on Belief Revision operators based on the use of logic programming with Answer Set semantics as a representation language. We present a set of postulates for Answer Set Revision with respect to…

Artificial Intelligence deals with the challenge of modeling commonsense reasoning. In the last fifteen years argument-based systems have came forward to meet this challenge as knowledge representation and reasoning tools able to model incomplete and conflicting information. We believe that…

(cont.) which is expected, given their additional knowledge resources. The respondents' urgency in looking for the relevant knowledge is the primary explanation for this difference between the two networks. This difference in knowledge networking among the different groups did not…

This thesis examines the evolution of Internet based knowledge networks (e-knowledge networks) in the domain of sustainable development. The objective of this thesis is to use an engineering systems approach to understand knowledge networks, identify the barriers to their sustainability…

Much Learning is done by way of studying precedents and exercises. A teacher supplies a story, gives a problem, and expects a student both to solve a problem and to discover a principle. The student must find the correspondence between…

An automatic disassembly cell requires of a
computer vision system for recognition and localization of
the products and each of theirs components. The detection
of occlusions adds more information to the knowledge base
to identify components and products, and generate…

There are many situations in which a very detailed low-level description encodes, through a hierarchical organization, a recognizable higher-order pattern. The macro-molecular structural conformations of proteins exhibit higher order regularities whose recognition is complicated by many factors. ARIADNE searches for…

Issues related to maternal mortality have generated a lot of empirical and theoretical information. However, despite the amount of work published on the topic, maternal mortality continues to occur at high rates and solutions to the problem are still not…

This paper presents a novel algorithm for learning in a class of stochastic Markov decision processes (MDPs) with continuous state and action spaces that trades speed for accuracy. A transform of the stochastic MDP into a deterministic one is presented…

We had previously shown that regularization principles lead to approximation schemes, as Radial Basis Functions, which are equivalent to networks with one layer of hidden units, called Regularization Networks. In this paper we show that regularization networks encompass a much…