AI and Cognitive Science ¿90

University of Ulster at Jordanstown 20¿21 September 1990
1. Auflage. 1991
ISBN: 978-3-540-19653-2
Verlag: Springer

Buch, Englisch, 392 Seiten, Paperback, Format (B × H): 170 mm x 244 mm, Gewicht: 708 g

Reihe: Workshops in Computing

This book contains the edited versions of papers presented at the 3rd Irish Conference on Artificial Intelligence and Cognitive Science, which was held at the University of Ulster at Jordanstown, Northern Ireland on 20-21 September 1990. The main aims of this annual conference are to promote AI research in Ireland, to provide a forum for the exchange of ideas amongst the different disciplines concerned with the study of cognition, and to provide an opportunity for industry to see what research is being carried out in Ireland and how they might benefit from the results of this research. Although most of the partiCipants at the conference came from universities and companies within Ireland, a positive feature of the conference was the extent of interest shown outside of Ireland, resulting in partiCipants from USA, Canada, Austria, and England. The keynote speakers were Professor David Chin, University of Hawaii, and Professor Derek Partridge, University of Exeter, and the topics included machine learning, AI tools and methods, expert systems, speech, vision, natural language, reasoning with uncertain information, and explanation. The sponsors of the conference were Digital Equipment Co (Galway) and the Industrial Development Board for Northern Ireland.

Zielgruppe

Research

Autoren/Hrsg.

Creaney, Norman

McTear, Michael F.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

Section 1: Artificial Intelligence — Tools and Methods.- What the Software Engineer Needs to Know About Al — and vice versa.- Developmental Support for Knowledge Based Systems.- Problem Description and Hypotheses Testing in Artificial Intelligence.- Section 2: Learning.- Machine Learning in Subject Classification.- A Test Bed for some Machine Learning Algorithms.- Section 3: Expert Systems.- Application of Expert Systems in Electrical Engineering.- Artificial Intelligence Applications in Geology: A Case Study with EXPLORER.- An Expert Assistant for High Frequency Electronic Circuit Design.- SWEEP: Social Welfare Entitlement Evaluation Program.- Architectural Issues in Knowledge-Based Signal Processing.- Section 4: Speech and Vision.- Neural Networks for Speech Recognition.- Using Observer-Controlled Movement and Expectations of Regularity to Recover Tridimensional Structure.- Measuring the ‘Rubber Rhomboid’ Effect.- Section 5: Cognitive Modelling.- Knowledge, Cognition and Acting in an Environment.- Section 6: Natural Language.- Natural Language Dialogues for Knowledge Acquisition.- Parsing English Directly into Propositional Representations.- SIMPR: Using Syntactic Processing of Text for Information Retrieval.- Very Large Lexicon Management System for Natural Language Generation.- Distributed Subsymbolic Representations for Natural Language: How Many Features do you Need?.- Section 7: Explanation.- Allowing Multiple Question Types to Influence the Resulting Explanation Structure.- The Construction of Explanations.- Section 8: Uncertainty.- Incomplete Information and Uncertainty.- Propagating Beliefs Among Frames of Discernment in Dempster-Shafer Theory.- Evidential Reasoning and Rule Strengths in Expert Systems.- Author Index.