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…

We show how to interoperate, semantically and inferentially, between the leading Semantic Web approaches to rules (RuleML Logic Programs) and ontologies (OWL/DAML+OIL Description Logic) via analyzing their expressive intersection. To do so, we define a new intermediate knowledge representation (KR)…

We examine semantic interoperability problems in the fixed income securities industry
and propose a knowledge representation architecture for context interchange
mediation to support dynamic integration of autonomous database, web, and
procedural sources of information. For sources and…

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…

The studies of anatomy and physiology are fundamental ingredients of medical education. This paper identifies six ways in which such functional knowledge serves as the underpinnings for general medical reasoning, and outlines the design of a computational model of common…

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…

The thesis explores architectural form generation through two behavior based artificial intelligence approaches: the communication of agents in an unpredictable simulation system, and the codification of information within an evolutionary process. Both concepts stem from the evaluation of potentially definable…

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…

In this thesis, I examine how spinning off new ventures from academic institutions works in an environment outside developed high tech clusters and how it affects models of ventures. I examine these questions by studying the case of Belgium. There…

What are the characteristics of the process by which an intent is transformed into a plan and then a program? How is a program debugged? This paper analyzes these questions in the context of understanding simple turtle programs. To understand…