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This unique volume focuses on computing systems that exhibit intelligent behavior. As such, it discusses research aimed at building a computer that has the same cognitive architecture as the mind — permitting evaluations of it as a model of the mind — and allowing for comparisons between computer performance and experimental data on human performance. It also examines architectures that permit large, complex computations to be performed — and questions whether the computer so structured can handle these difficult tasks intelligently.
Contents: Preface. Part I: Cognitive Psychology. J.R. Anderson, The Place of Cognitive Architectures in a Rational Analysis. H.A. Simon, Cognitive Architectures and Rational Analysis: Comment. J.L. McClelland, E. Jenkins, Nature, Nurture and Connections: Implications of Connectionist Models for Cognitive Development. P.S. Rosenbloom, A. Newell, J.E. Laird, Towards the Knowledge Level in Soar: The Role of the Architecture in the Use of Knowledge. W. Schneider, W.L. Oliver, An Instructable Connectionist/Control Architecture: Using Rule-Based Instructions to Accomplish Connectionist Learning in a Human Time Scale. K. VanLehn, W. Ball, Goal Reconstruction: How Teton Blends Situated Action and Planned Action. Z.N. Pylyshyn, The Role of Cognitive Architectures in Theories of Cognition. Part II: Artificial Intelligence. R.A. Brooks, How to Build Complete Creatures Rather than Isolated Cognitive Simulators. J.G. Carbonell, C.A. Knoblock, S. Minton, Prodigy: An Integrated Architecture for Planning and Learning. M.R. Genesereth, A Comparative Analysis of Some Simple Architectures for Autonomous Agents. B. Hayes-Roth, Making Intelligent Systems Adaptive. T.M. Mitchell, J. Allen, P. Chalasani, J. Cheng, O. Etzioni, M. Ringuette, J.C. Schlimmer, Theo: A Framework for Self-Improving Systems. W.J. Clancey, The Frame of Reference Problem in the Design of Intelligent Machines.