George Luger, Computer Science, 277-3204, FEC 349E, luger@cs.unm.edu

Tom Caudell, Dept of Electrical & Computer Engineering

Tim Goldsmith, Dept of Psychology

Fred Schuller, Dept. of Philosophy

Akaysha Tang, Depts of Psychology and Computer Science

Lance Williams, Dept of Computer Science

Ron Yeo, Dept of Psychology

by George Luger with P. Johnson, C. Stern, J. Neuman, & R. Yeo

Cognitive Science is concerned with the interdisciplinary effort of Cognitive Psychologists, Computer Scientists, Electrical Engineers, Linguists, Neuroscientists, Mathematicians, and Philosophers to identify the essential properties of intelligent systems. The basic assumption shared by this diverse group of scientists is that intelligence is a natural category, and as such, has a fundamental set of principles that describe its functioning. In fact, it requires the combined skills of this interdisciplinary scientific community to elucidate the issues surrounding intelligence. The lecturers present intelligence from the physical symbol system, connectionist, neurophysiological, philosophical, and cognitive perspectives.

Given the wide range of students taking this course we do not require any specific prerequisites, except that students be at the 400 course level in your own department. If you have any questions, give Prof Luger a call (or e-mail luger@cs.unm.edu). A more detailed syllabus is available.

• General Background

• Intelligence as a Natural Category

• Definitions of Intelligence

• Scope of the Course

Readings: Luger, Chapter 1

• Folk Psychology

• Philosophical & Methodological Behaviorism

• The Neuro-Science approach

• The Automated Formal System

Readings: Luger, Chapter 2

• Why Representations?

• Computational tools

• A psychological Methodology

• Examples, including the neural network

Readings: Luger, Chapter 3

• From viable to valid models of mind

• Weak and strong equivalence

• The methodology

• Is strong equivalence possible?

Readings: Luger, Chapter 4

• The Celular Basis of Learning

• Levels of Neurological Organization

• Cortical Resourses and Connectivity

• Parallel Computations and Mappings

Readings: Luger, Chapter 5

• The Semantic Network

• Conceptual Dependencies and Scripts

• Frames and Schemas

• Objects and Inheritance Systems

Readings: Luger, Part II, Ch 6

• The Problem of Learning

• Genetic and Emergent Models

• Language Generation and Understanding

• Semanticis, Pragmatics, and Reference

Readings: Luger, Part V, Ch 14 & 15

• Introduction

• The Connectionist Models

• Neural Realism & Neural Network Approaches

• Extensions and Limitations

Readings: Luger, Part III, Ch 11 & 12

• Newell/Simon vs Connectionist Approaches

• Architectures for Multi-Agent Problem Solving

• The Limitations of the Scientific Method

• Context and the Role of Society

Readings: Luger, Part IV, Chapter 16

• Semantic Grounding Issues

• Philosophical Challenges

• Strong Equivalence Revisited

• Summary of Progress in Cognitive Science