The field of cognitive science overlaps AI. Cognitive scientists study the nature of intelligence from a psychological point of view, mostly building computer models that help elucidate what happens in our brains during problem solving, remembering, perceiving, and other psychological processes. One major contribution of AI and cognitive science to psychology has been the information processing model of human thinking in which the metaphor of brain-as-computer is taken quite literally.
Artificial Intelligence Tutorial Review. From Eyal Reingold and Johnathan Nightingale at the University of Toronto. "Welcome to the PSY371 Artificial Intelligence tutorial review. These pages were developed for the use of psychology students interested in the field of Artificial Intelligence, especially as it relates to the ongoing investigations in psychology aimed at understanding the human mind....This review has been designed with the expectation that its readers are new to the area, and care is taken to explain concepts fully. The review should provide an interesting and accessible introduction for beginners, but may be somewhat redundant for readers with more background in the area. Nevertheless, more advanced readers may find interesting links and demonstrations throughout the review. Also, in hopes of keeping the tutorial accessible, many of the more technical issues in AI have been simplified or avoided, with more emphasis being put on conceptual developments and interactive examples."
What is Cognitive Science. From Cognitive Science Major at UC Berkeley. "Cognitive Science is an interdisciplinary field that has arisen during the past decade at the intersection of a number of existing disciplines, including psychology, linguistics, computer science, philosophy, and physiology. The shared interest that has produced this coalition is understanding the nature of the mind. This quest is an old one, dating back to antiquity in the case of philosophy, but new ideas are emerging from the fresh approach of Cognitive Science."
Cognitive Science entry in The Stanford Encyclopedia of Philosophy. By Paul Thagard. A solid overview plus links for further study.
USC's Michael Arbib. By Eric Smalley. Technology Research News (October 3, 2005). "Technology Research News Editor Eric Smalley carried out an email conversation with Michael Arbib, the Fletcher Jones Professor of Computer Science and a Professor of Biological Sciences, Biomedical Engineering, Electrical Engineering, and Neuroscience and Psychology at the University of Southern California (USC) in September 2005. ... Throughout his career Arbib has encouraged an interdisciplinary environment where computer scientists and engineers can talk to neuroscientists and cognitive scientists."
Cognitive Science. By William J. Rapaport. Draft of the article in Encyclopedia of Computer Science, 4th edition; Anthony Ralston, Edwin D. Reilly, and David Hemmindinger, editors (New York: Grove's Dictionaries, 2000): 227 - 233. "The notion that mental states and processes intervene between stimuli and responses sometimes takes the form of a 'computational' metaphor or analogy, which is often used as the identifying mark of contemporary cognitive science: The mind is to the brain as software is to hardware; mental states and processes are (like) computer programs implemented (in the case of humans) in brain states and processes. ... Insofar as the methods of investigation are taken to be computational in nature, computer science in general and artificial intelligence in particular have come to play a central role in cognitive science."
Cognitive Science Dictionary. Maintained by Michael R. W. Dawson and David A. Medlar of the University of Alberta.
Cognitive Psychology. An overview from Humboldt State University. "In studying the design of computers that learn, we have gained much knowledge about the cognitive processes within us. Newell and Simon conrtibuted much in educating cognitive psychologists on the implications of artificial intelligence, and in educating the artificial intelligence people on the implications of cognitive psychology. A host of concepts, such as informatin processing, short-term memory, long-term memory, etc., has been taken from computer science and used in cognitive psychological theories."
Cognitive Theory and System Design. Just one of the pages in Mind Models: Artificial Intelligence Discovery At Carnegie Mellon, an online exhibit from Carnegie Mellon's University Archives. "For a half century, Carnegie Mellon University has been a leader in the research and design of artificial intelligence (AI) - the creation of 'thinking machines'. Many of CMU's achievements came from pioneering work by professors Herbert A. Simon and Allen Newell."
Intelligent Systems and their Societies: an e-book. By Walter Fritz. "We can look at human beings from many points of view, as biological beings, employees, fathers, or mothers, but when we look at the decision process for selecting an action, we should view them as intelligent systems. Analyzing artificial intelligent systems gives us a new understanding of both human intelligence and other intelligences. However, it is difficult to study the mind with a similar one--namely ours. We need a better mirror. As you will see, in artificial intelligent systems we have this mirror...." - from the Foreword.
SOAR.
"Soar means different things to different people, but it can basically
be considered in three different ways: 1. A theory of cognition. As such
it provides the principles behind the implemented Soar system. 2. A set
of principles and constraints on (cognitive) processing. Thus, it provides
a (cognitive) architectural framework, within which you can construct
cognitive models. In this view it can be considered as an integrated architecture
for knowledge-based problem solving, learning and interacting with external
environments. 3. An AI programming language." FAQ (G1) What is Soar?,
from the Soar
Frequently Asked Question List. Maintained by Frank E. Ritter, Gordon
D. Baxter, Marios Avaramides, and Alexander B. Wood.
Readings Online
A Computational Foundation for the Study of Cognition. By David J. Chalmers, Department of Philosophy, University of Arizona. (1994). "A careful analysis of computation and its relation to cognition suggests that the ambitions of artificial intelligence and the centrality of computation in cognitive science are justified."
Brain learns like a robot - Scan shows how we form opinions. By Tanguy Chouard. Nature Science Update (June 10, 2004). "Researchers may have pinpointed the brain regions that help us work out good from bad. And their results suggest that humans and robots are more alike than we may care to admit, as both use similar strategies to make value judgements. ... The team also plotted brain activity on a graph to give a mathematical description of processes that underlie the formation of value judgements. The patterns they saw resembled those made by robots as they learn from experience. 'The results were astounding,' says study co-author Peter Dayan. 'There was an almost perfect match between the brain signals and the numerical functions used in machine learning,' he says. This suggests that our brains are following the laws of artificial intelligence."
Cognitive Science issue of Crossroads (Winter 2003 - 10.2). Articles include:
- At the Crossroads of Computers and the Mind. Introduction to the special issue by Ronald Laurids Boring. "First, what exactly is cognitive science? Cognitive science is the study of the mind. The problem is that mind means different things to different people. To a computer scientist, the mind might be something that can be simulated through software or hardware. So, cognitive science would be synonymous with artificial intelligence. On the other hand, to a cognitive psychologist, the mind is the key to understanding human or animal behavior. To a cognitive neuroscientist, the mind is about the brain and its neurological underpinnings. To a philosopher of mind, cognitive science is the culmination of thousands of years of philosophical tradition. To a cognitive linguist, cognitive science is about how thinking and language interact. The list goes on."
- A Day in the Life of... Douglas Hofstadter. "Most people in cognitive science have no concept of how deep microworlds can be, because some years ago it was unfortunately very trendy to pooh-pooh them, and many people fell for the propaganda that microworlds were outmoded and couldn't provide deep insight into thinking. How wrong they were!"
- The Humanoid Robot Cog. By Naveed Ahmad. "COG was designed and built to emulate human thought processes and experience the world as a human. Brooks and his team further assumed that people would find it easier to interact with a robot and aid the robot in its learning process when the robot could respond in a somewhat human way. Consequently, the machine should have limbs, sensory organs, and a physical resemblance to humans. Unlike other artificial intelligence systems, like medical expert systems, COG was meant to test theories of human cognition and developmental psychology."
Christopher Longuet-Higgins - Cognitive scientist with a flair for chemistry. Obituary by Chris Darwin.The Guardian (June 10, 2004). "Christopher Longuet-Higgins, who has died aged 80, was not only a brilliant scientist in two distinct areas - theoretical chemistry and cognitive science - but also a gifted amateur musician, keen to advance the scientific understanding of the art. ... In 1967, as a result of a growing interest in the brain and the new field of artificial intelligence, Christopher made a dramatic change in direction and moved to Edinburgh to co-found the department of machine intelligence and perception, together with Richard Gregory and Donald Michie. It was Christopher who, in 1973, was the first to name this field more broadly as 'cognitive science'."
What Are Intelligence? And Why? 1996 AAAI Presidential Address by Randall Davis. AI Magazine, 19(1): Spring 1998, 91-111. "This article, derived from the 1996 American Association for Artificial Intelligence Presidential Address, explores the notion of intelligence from a variety of perspectives and finds that it "are" many things. It has, for example, been interpreted in a variety of ways even within our own field, ranging from the logical view (intelligence as part of mathematical logic) to the psychological view (intelligence as an empirical phenomenon of the natural world) to a variety of others. One goal of this article is to go back to basics...."
How Can Psychology Help Artificial Intelligence? By Alvaro del Val. Interfaces da Psicologia, University of Evora, Portugal (1999). "In particular, I'll suggest that cognitive psychology, in order to be useful to AI, needs to study common-sense knowledge and reasoning in realistic settings; and to focus less in errors in performance in favour of studying how people do well the things they do well. " [Other formats can be accessed from this paper's entry in the ResearchIndex.]
The robot that thinks like you... Scientists built a robot that thinks like we do and set it loose to explore the world. New Scientist discovers what happened next By Douglas Fox. New Scientist (November 5, 2005; subscription req'd.; Issue 2524). "The infant I am watching wander around its rather spartan playpen in the Neurosciences Institute (NSI) in La Jolla, California, is a more limited creature. It is a trashcan-shaped robot called Darwin VII, and it has just 20,000 brain cells. Despite this, it has managed to master the abilities of a 18-month-old baby -- a pretty impressive feat for a machine. ... Darwin VII is the fourth in a series of robots that Jeff Krichmar and his colleagues at NSI have created in a quest to better understand how our own brains work. ... The idea of an artificial neural network that could perform computations was proposed as long ago as 1943, by Warren McCullough and Walter Pitts at the University of Illinois. ... [I]n the past few years, neuroscientists and AI researchers have started collaborating more closely, and their labours are beginning to bear fruit. Their conclusions challenge two decades of research into artificial neural networks."
- Visit the Neurosciences Institute ... read about their 5 strategic initiatives (Theoretical Work on Brain Function, Complex Systems, Theoretical and Experimental Program, Consciousness, and Learning Machines) ... and meet Jeffrey L. Krichmar and Nomad & Darwin!
Safe and Sound: Artificial Intelligence in Hazardous Applications. By John Fox and Subrata Das. AAAI Press. The following excerpt is from the Preface which is available online: "This book is about the nature of cognition, both natural and artificial. It has grown out of a program of research into intelligent functions like reasoning, problem solving and decisionmaking. These are well-established research topics, but our program is unusual in its focus on the integration of these and related cognitive processes. Many cognitive scientists seek a unified theory of their subject matter but, as in many other fields of scientific enquiry, the discipline tends to fragment into more and more specialist areas and unification eludes us. Our long-term aim is to develop intellectual and methodological tools that will foster a unified cognitive science."
Sex Differences in the Brain. By Doreen Kimura. (Scientific American, May 13, 2002). "Men and women display patterns of behavioral and cognitive differences that reflect varying hormonal influences on brain development."
- Check out our related toon!
- also see: Sexes handle emotions differently. BBC (July 23, 2002), and Sexes 'brains work differently.' BBC (July 8, 2001).
Brain and Cognitive Sciences courses available from MIT OpenCourseWare, "a free and open educational resource for faculty, students, and self-learners around the world. OCW supports MIT's mission to advance knowledge and education, and serve the world in the 21st century." include:
- 9.29J / 8.261J Introduction to Computational Neuroscience: Spring 2002
- 9.52-C Computational Cognitive Science: Spring 2003
- 9.611J Natural Language and the Computer Representation of Knowledge: Spring 2003
- 9.67 Object and Face Recognition: Spring 2001
- 9.68 Affect: Biological, Psychological, and Social Aspects of "Feelings'': Spring 2002
- 9.913-C Pattern Recognition for Machine Vision: Spring 2002
- Also see the selection of Electrical Engineering and Computer Science courses.
Humans That Think: A Future Trialogue. By Pamela McCorduck. AI Magazine 4(3): Fall 1983, 35. " We can expect, then, a conference such as this in fifty years ( a hundred years, no need to frame it precisely) to feature as its centerpiece a panel discussion among computers on the fascinating topic of whether humans can really be said to think. Picture three computers, named for no particular reason, Edward, Marvin and Seymour, debating before a learned group such as yourselves."
Creating a Robot Culture - An Interview with Luc Steels. The well-known researcher shares his views on the Turing test, robot evolution, and the quest to understand intelligence. By Tyrus L. Manuel. IEEE Intelligent Systems (May/June 2003). "Computers and robots are used as experimental platforms for investigating issues about intelligence. Researchers who are motivated in this way, and I am one of them, try to make contributions to biology or the cognitive sciences. ... AI has had an enormous impact on how we think today about the brain and the mechanisms underlying cognitive behavior."
Programs of the Mind. Review by Gary Marcus. Science Magazine (June 4, 2004; subscription required). "Eric Baum's What Is Thought? [MIT Press, Cambridge, MA, 2004], consciously patterned after [Erwin] Schrödinger's book [What Is Life?], represents a computer scientist's look at the mind. Baum is an unrepentant physicalist. He announces from the outset that he believes that the mind can be understood as a computer program. Much as Schrödinger aimed to ground the understanding of life in well-understood principles of physics, Baum aims to ground the understanding of thought in well-understood principles of computation. In a book that is admirable as much for its candor as its ambition, Baum lays out much of what is special about the mind by taking readers on a guided tour of the successes and failures in the two fields closest to his own research: artificial intelligence and neural networks. ... Advocates of what the philosopher John Haugeland famously characterized as GOFAI (good old-fashioned artificial intelligence) create hand-crafted intricate models that are often powerful yet too brittle to be used in the real world. ... At the opposite extreme are researchers working within the field of neural networks, most of whom eschew built-in structure almost entirely and rely instead on statistical techniques that extract regularities from the world on the basis of massive experience."
AI and the Impending Revolution in Brain Sciences. Powerpoint slides of Tom Mitchell's AAAI Presidential Address, August 2002. [An associated video file is also available from his home page.] "Thesis of This Talk: The synergy between AI and Brain Sciences will yield profound advances in our understanding of intelligence over the coming decade, fundamentally changing the nature of our field."
Whatever happened to machines that think? By Justin Mullins. New Scientist (April 23, 2005; Issue 2496: pages 32 - 37). "Where could the secret to intelligence lie? According to [Tom] Mitchell, the human brain is the place to look. He has been using functional magnetic resonance imaging (fMRI) to see which parts of the brain become active when a person thinks about a specific object. He has found that when people are asked to imagine a tool such as a hammer or a building such as a house, the same areas of the brain are activated as when they are shown a picture of these objects. He has also found that the area activated for each object - hammer or house - differs by a discernable amount depending on the object."
The Isaac Newton of logic - It was 150 years ago that George Boole published his classic The Laws of Thought, in which he outlined concepts that form the underpinnings of the modern high-speed computer. By Siobhan Roberts. The Globe and Mail (March 27, 2004; page F9). "It was 150 years ago that George Boole published his literary classic The Laws of Thought, wherein he devised a mathematical language for dealing with mental machinations of logic. It was a symbolic language of thought -- an algebra of logic (algebra is the branch of mathematics that uses letters and other general symbols to represent numbers and quantities in formulas and equations). ... 'Boole was the first cognitive scientist,' says Keith Devlin, executive director of the Center for the Study of Language and Information at Stanford University."
AI, Cognitive Science and Robotics. Maintained by Uwe R. Zimmer.
Academic Programs in Cognitive Science collection from the Cognitive Science Society.
Celebrities of Cognitive Science. Maintained by Martin Ryder, University of Colorado at Denver. Links to homepages and papers of leading researchers.
"The Center for Research on Concepts and Cognition is an interdisciplinary center for research in cognitive science, directed by Douglas Hofstadter. CRCC is affiliated with the Cognitive Science Program at IU, and has close ties with the Computer Science Department. CRCC research focuses mainly on emergent computational models of creative analogical thinking and its subcognitive substrate -- namely, fluid concepts."
- Also see the Program in Cognitive Science at Indiana University.
The Center for the Neural Basis of Cognition (CNBC), a joint project of Carnegie Mellon University and the University of Pittsburgh.
The Cognition and Affect Project at the University of Birmingham School of Computer Science's Cognitive Science Research Centre.
Cognitive Science at the University of Edinburgh.
Cognitive Science Department (CSD) at Rensselaer Polytechnic Institute. "Having been launched in 2002, the Cognitive Science Department (CSD) at Rensselaer is the world's newest department of Cognitive Science. ... Our research and doctoral program is aimed at the creation of an integrated, interdisciplinary department whose research and teaching is focused on three powerful, driving ideas: * 'Next generation' artificial intelligence (AI): the design and construction of fully integrated artificial cognitive systems that reach across the full spectrum of cognition, from low-level perception/action to high-level reasoning, implemented in significant part on the basis of empirical data regarding natural cognitive systems. * 'Next generation' computational cognitive modeling: the design and implementation of cognitive architectures that extend beyond currently available architectures (e.g., ACT-R and SOAR) toward Newell’s original dream of an architecture that accurately reflects the full range of cognitive processes present in natural cognitive systems. * Cognitive engineering: engineering the interface between natural cognitive systems and task environments by, once again, exploiting empirical data concerning natural cognitive systems. These three ideas are the core of a philosophy of doctoral education that we call Teaching Integrated Cognitive Systems (TICS)."
- Also see:
- the department's Minds & Machines Program: "an applied cognitive science undergraduate program. Students who enter the Minds & Machines Program perform cutting-edge scientific research into the nature of reasoning, perception, memory, and learning, create intelligent artificial agents and smart enabling technology, and address philosophical questions about the fundamental nature of our mind and the ethical implications of cognitive technology."
- RAIR: the Rensselaer Artificial Intelligence and Reasoning Laboratory
- Building a Better Brain. By Sheila Nason. Rensselaer Research Quarterly (Winter 2004).
Cognitive Science Summaries. Edited by Jim Davies. "This site has summaries of artificial intelligence and cognitive science articles and book chapters. It is intended to help find papers to read, or as a reminder of the gist of a paper you've already read."
Cognitive Systems - a UK Foresight programme project designed "A) to examine recent progress in two major areas of research - computer science and neuroscience (and their related fields) - to understand whether progress in understanding cognition in living systems has new insights to offer those researching the construction of artificial cognitive systems; B) to scope likely developments in these fields over the next decade, and in particular to scope the likely rate of progress in our capability to build artificial cognitive systems; C) to articulate significant conclusions to a wider audience."
Developmental
Robotics. Sony Computer Laboratory Paris. 
"Generating
plausible models for the processes underlying children's development in
the first years of their life is a challenging scientific issue at the
crossroads of neuroscience, learning theories and developmental psychology.
Children seem to acquire new know-how in a continuous and open-ended manner.
A large amount of work describes how new skills seem to build one upon
another, suggesting a continuum between sensory-motor development and
higher cognitive functions. But very few plausible low-level mechanisms
exist to explain how such skills emerge or self-organize. Studying development
is intrinsically difficult because of the complex interplay between embodiment,
learning mechanisms and environmental dynamics. A relevant integrative
approach can be pursued by viewing development as a complex system the
dynamics of which can be studied with embodied models. In order to capture
part of the open-ended nature that characterizes children's development,
we design new biologically-inspired architectures to control autonomous
robots. ... This approach might not only help us understand the mechanisms
underlying human development, but it might also provide radically new
techniques for building intelligent robots. Indeed, as opposed to the
work in classical artificial intelligence in which engineers impose pre-defined
anthropocentric tasks to robots, the techniques we develop endow the robots
with the capacity of deciding by themselves which are the activities that
are maximally fitted to their current capabilities."
Institute for Research in Cognitive Science (IRCS), site of the National Science Foundation Science and Technology Center for Research in Cognitive Science.
MIT OpenCourseWare Brain and Cognitive Sciences courses available online.
Soar Technology, Inc. "The foundation for all of Soar Technology’s projects is rooted in cognitive science. This primarily includes behavior, cognition, perception, memory, performance, learning, and emotion. Much of this scientific base is encoded within Soar, a computational cognitive architecture that enables the creation of autonomous software agents capable of sophisticated reasoning while utilizing large amounts of human-level knowledge." - from Cognitive Research & Architectures
- Assistive Technologies (assisted cognition)
- CreativityEmotion
- General Index to AI in the news: Cognitive Science
- Nature of Intelligence
The 100 Most Influential Works in Cognitive Science from the 20th Century as selected by a panel of judges who are both faculty of the University of Minnesota and members of its Center for Cognitive Sciences.
Adelson, B. 1984. When Novices Surpass Experts: The Difficulty of a Task May Increase with Expertise. Journal of Experimental Psychology: Learning, Memory & Cognition 10: 483-495.
Anderson, J. R. 1983. The Architecture of Cognition. Cambridge, MA: Harvard University Press.
Arbib, Michael A., editor. 1995. Handbook of Brain Theory and Neural Networks. Cambridge, MA: MIT Press. Hundreds of experts contribute articles charting progress in the study of how the brain works and how we can build intelligent machines.
Arkes, H. R., and M. R. Freedman 1984. A Demonstration of the Costs and Benefits of Expertise in Recognition Memory. Memory & Cognition 12: 84-89.
Boden, Margaret A. 1996. Artificial Genius. Discover 17: 104-107.
Margaret A. Boden: Creativity and Artificial Intelligence. Artificial Intelligence 103(1-2): 347-356 (1998). Boden describes how AI techniques can be used to create new ideas.
Chi, M. T. H., P. J. Feltovich and R. Glaser. 1981. Categorization and Representation of Physics Problems by Experts and Novices. Cognitive Science 5: 121-152.
Chi, M. T. H., and R. D. Koeske. 1983. Network Representation of a Child's Dinosaur Knowledge. Developmental Psychology 19: 29-39.
Clark, Andy. 1997. Being There: Putting Brain, Body, and World Together Again. Cambridge, MA. and London: MIT Press.
Colby, Kim. 1967. Computer Simulation of Change in Personal Belief Systems. Behavioral Science 12 (May 1967): 248-253.
De Groot, A. D. 1978. Thought and Choice in Chess, 2nd edition. Paris and The Hague: Mouton.
Doyle, Jon. 1983. What is Rational Psychology? Toward a Modern Mental Philosophy. AI Magazine 4 (3): 50-53.
Epstein, Robert. 1992. The Quest for the Thinking Computer. AI Magazine 13 (2): 81-95. Article is accompanied by the transcript of the session that won the Loebner Prize Competition-Joseph Weintraub's computer program PC Therapist.
Feltovich, Paul J., Kenneth M. Ford, and Robert R. Hoffman, editors. 1997. Expertise in Context: Human and Machine. Menlo Park, CA. and Cambridge, MA: AAAI Press/MIT Press.
Fischler, Martin, and Oscar Firschein. 1987. Intelligence: The Eye, the Brain, and the Computer. Reading, MA: Addison-Wesley. An overview intended for a general readership.
Ford, Kenneth, Clark Glymour, and Patrick Hayes, editors. 1995. Android Epistemology. Menlo Park, CA: AAAI Press. Approaches artificial intelligence and cognitive psychology as a unified endeavor, with AI focused on possible ways of engineering intelligence and cognitive science. Sixteen essays by computer scientists and philosophers.
Gleitman, Lila R., and Mark Liberman. 1995. An Invitation to Cognitive Science. Vol. 1: Language. Cambridge, MA: MIT Press/Bradford Books.
Guterl, Frederick V. 1997. Beauty and Magnets. Discover 18 (March 1997): 38-40.
Hofstadter, Douglas R. 1979. Godel, Escher, Bach: An Eternal Golden Braid. New York: Basic Books.
Haugeland, John., editor. 1997. Mind Design II: Philosophy, Psychology, Artificial Intelligence. Cambridge, MA: MIT Press.
Holtzman, Steven R. 1995. Painting By Number. Technology Review 98: 60-68.
Johnson, George. 1997. Undiscovered Bach? No, A Computer Wrote It. In Proceedings of the New York Times, Section F, pp. 1-2.
Johnson, George. 1997. The Artist's Angst is All in Your Head. In Proceedings of the New York Times, Section 4, p. 16.
Johnson-Laird, P. N. 1988. The Computer and the Mind: An Introduction to Cognitive Science. Cambridge, MA: Harvard University Press.
Kahneman, D., P. Slovic, and A. Tversky. 1982. Judgements Under Uncertainty: Heuristics and Biases. Cambridge: Cambridge University Press. Includes a classic paper "Causal Schemata in Judgements Under Uncertainty" by Tversky and Kahneman.
Kolodner, J. L. 1983. Towards an Understanding of the Role of Experience in the Evolution from Novice to Expert. International Journal of Man-Machine Studies 19: 497-518.
Kosslyn, Stephen M., and Daniel N. Osherson. 1995. An Invitation to Cognitive Science. Vol. 2: Visual Cognition. Cambridge, MA: MIT Press/Bradford Books.
Kurzweil, Raymond, et. al 1990. The Science of Art. In the Age of the Intelligent Machine, ed. Kurzweil, Raymond, 351-395. Cambridge, MA: MIT Press.
Luger, George F. 1994. Cognitive Science: The Science of Intelligent Systems. Academic Press.
Mayer, R. F. 1988. From Novice to Expert. In Handbook of Human-Computer Interaction, ed. Holander, M., 569-580. Amsterdam: North-Holland.
Means, M. L., and J. F. Voss 1985. Star Wars: A Developmental Study of Expert and Novice Knowledge Structures. Journal of Memory and Language 24: 746-757.
Miller, George A. 1956. The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information. The Psychological Review 63 (March 1956): 81-97. A classic paper.
Myles-Worsley, M., W. A. Johnston, and M. A. Simons 1988. The Influence of Expertise on X-Ray Image Processing. Journal of Experimental Psychology: Learning, Memory & Cognition 14: 553-557.
Newell, Allen. 1990. Unified Theories of Cognition. Cambridge, MA: Harvard University Press.
Newell, Allen. 1988. Putting it All Together. In Complex Information Processing: The Impact of Herbert A. Simon, ed. D. Klahr and K. Kotovsky, Hillsdale, NJ: Erlbaum and Associates.
Newell, Allen, and Herbert Simon. 1972. Human Problem Solving. Englewood Cliffs, NJ: Prentice-Hall.
Novick, L. R. 1988. Analogical Transfer, Problem Similarity, and Expertise. Journal of Experimental Psychology: Learning, Memory & Cognition 14: 510-520.
Port, R., and T. van Gelder 1995. Mind as Motion: Explorations in the Dynamics of Cognition. Cambridge, MA: Bradford Books/MIT Press.
Scarborough, Don, and Saul Sternberg. 1998. An Invitation to Cognitive Science. Vol. 4: Methods, Models, and Conceptual Issues. Cambridge, MA: MIT Press/Bradford Books. Covers artificial intelligence, neural networks, animal cognition, signal detection theory, computational models, cognitive neuroscience and more.
Scheines, Richard. 1988. Automating Creativity. In Aspects of Artificial Intelligence, ed. Fetzer, James H., Dordrecht, Netherlands: Kluwer Academic Press.
Shanteau, J. 1987. Psychological Characteristics of Expert Decision Makers. In Expert Judgment and Expert Systems, ed. Mumpower, J. L., O. Renn, L. D. Phillips, et al., 289-304. Berlin: Springer-Verlag.
Smith, Edward E., and Daniel N. Osherson. 1995. An Invitation to Cognitive Science. Volume 3: Thinking. Cambridge, MA: MIT Press/Bradford Books.
Steinert-Threlkeld, Tom. Marvin Minsky Wants Machines To Get Emotional. ZDNet/Interactive Week. (February 25, 2001). "Because the main point of the book [The Emotion Machine] is that it's trying to make theories of how thinking works. Our traditional idea is that there is something called 'thinking' and that it is contaminated, modulated or affected by emotions. What I am saying is that emotions aren't separate."
Sternberg, Robert J., editor. 1998. The Nature of Cognition. Introduces major themes in the field by contrasting alternative approaches and synthesizing them. Covers general issues, representation and process, methodology, kinds of cognition, and group and individual differences. Cambridge, MA: MIT Press/Bradford Books.
Stewart, Doug. Interview with Herbert Simon, June 1994. Omni Magazine. See excerpt above. [No longer available online.]
Stillings, Neil A., Steven Weisler, Christopher Chase, Mark Feinstein, Jay Garfield, and Edwina Rissland. 1995. Cognitive Science: An Introduction. 2nd edition. Cambridge, MA: MIT Press/Bradford Books. A comprehensive undergraduate text that includes ideas in psychology, philosophy, linguistics, and artificial intelligence, and covers the new connectionist approach as well as the classical symbolic approach, with a new chapter on advances in neuroscience.
Stonier, Tom. 1992. Beyond Information: the Natural History of Intelligence. London and New York: Springer-Verlag. Thagard, Paul, editor. 1998. Mind Readings: Introductory Selections on Cognitive Science. Cambridge, MA: MIT Press/Bradford Books. Recent accessible readings in the field of cognition, both from the point of view that thinking is a computational procedure on a mental representation and from challengers to that point of view.
Thagard, Paul 1996. Mind: Introduction to Cognitive Science. Cambridge, MA: Bradford Book/MIT Press.
Ullman, Ellen. 2002. Programming the Post-Human: Computer science redefines "life." Harper's, Vol. 305, No. 1929: 60-70. "Ants are not generally thought of as being particularly smart. But as a model they have one enormous advantage over human brains: an explanation of how apparent complexity can arise without an overseeing designer. A group of dumb ant produces the complexity of the ant colony - an example of organizational intelligence without recourse to the perennial difficulties of religion or philosophy. Again, the source for this key idea seems to be Herbert Simon. The third chapter of The Sciences of the Artificial opens by describing an ant...." [p. 64]
Winograd, T. and F. Flores. 1986. Understanding Computers and Cognition: A New Foundation for Design. Norwood, NJ: Ablex.