PS 341

UNIVERSITY OF WARWICK

DEPARTMENT OF PSYCHOLOGY

COURSE OUTLINE 1995/96

COGNITIVE SCIENCE: Thought and Language

Teaching Staff

Dr George Dunbar

Student Population

Year III Single Honours Psychology students

Joint Honours Education/Psychology students

Joint Honours Psychology/Philosophy students

Joint Honours Philosophy/Psychology students

Honours Chemistry with Psychology students

YEAR IV 2 + 2 Social Studies students

Work Load

A weekly lecture or workshop, plus a seminar.

Method of Assessment

EITHER: One, one and one-half hour unseen examination. 100%

OR: Two essays (each 2,500 words) 100%

Course Credit

For Single Honours and all Psychology joint degrees this course weight is 15 CATS credits (12.5%)

Required Work

Students are required to contribute to debates and to participate in practical work (cognitive modelling).

COURSE OBJECTIVES AND CONTENT

This course examines basic processes of thought and language, emphasising experimental and computational approaches. In particular, studies of adult reasoning and problem solving are considered in relation to the literature on cognitive development, and the relationship between conceptual structure and language understanding is explored. The role of modelling is discussed critically. Students are also given a basic practical introduction to cognitive modelling, and have the opportunity for hands-on encounters with "intelligent" programs. (Performance in the programming exercises is not assessed formally.)

Lecture Titles

L1 Introduction - why cognitive science?

L2 Knowledge representation

L3 Reasoning

L4 Problem solving

L5 Lisp workshop - basic skills

L6 Concept learning and concept acquisition

L7 Search and machine learning

L8 Lisp workshop - production systems and connectionist models

L9 Concepts and language understanding

L10 Common-sense reasoning - the Yale Shooting Problem

READING

MANKTELOW & OVER, (1990), Inference and Understanding. Routledge.

MURPHY, G L, (1993), Theories and Concept Formation. In Categories and Concepts: Theoretical views and Inductive Data Analysis. Academic Press.

NILSSON, (1991), Logic and Artificial Intelligence. Artificial Intelligence 47, pp 31-56.

PATTERSON, DAN W, (1990), Introduction to Artificial Intelligence and Expert Systems. Prentice Hall International Edition.

SCHANK, R C, COLLINS, C G & HUNTER, L E, (1986), Transcending inductive category formation in learning. Brain and Behavioural Sciences, 9 (639-686).

GO22/95/96