This article seizes an opportune time to honor Marvin and his contributions and influence in artificial intelligence, science, and beyond. The article provides readers with some personal insights of Minsky from Danny Hillis, John McCarthy, Tom Mitchell, Erik Mueller, Doug Riecken, Aaron Sloman, and Patrick Henry Winston -- all members of the AI community that Minsky helped to found. The article continues with a brief resume of Minsky's research, which spans an enormous range of fields. It concludes with a short biographical account of Minsky's personal history.
To build a machine that has "common sense" was once a principal goal in the field of artificial intelligence. But most researchers in recent years have retreated from that ambitious aim. We are convinced, however, that no one such method will ever turn out to be "best," and that instead, the powerful AI systems of the future will use a diverse array of resources that, together, will deal with a great range of problems. To build a machine that's resourceful enough to have humanlike common sense, we must develop ways to combine the advantages of multiple methods to represent knowledge, multiple ways to make inferences, and multiple ways to learn.
THE FORMAL MECHANICS OF MIND: Stephen N. Thomas THE COGNITIVE PARADIGM: Marc De Mey ANALOGICAL THINKING: MYTHS AND MECHANISMS: Robin Anderson EDUCATION AND ARTIFICIAL INTELLIGENCE: Tim O'Shea Published later: GÖDEL ESCHER BACH: Douglas Hofstadter BRAINSTORMS: Daniel Dennett (Also published in the USA by Humanities Press, 1978) Since 1991, the author Aaron Sloman has been at The School of Computer Science University of Birmingham, UK (Now: Honorary professor of Artificial Intelligence and Cognitive Science.) HTML and PDF'book' Versions (Some indentation lost in PDF version) In July 2015 the online parts were combined to form this electronic book (with internal links) in HTML and PDF: Separate chapters found online are now out of date. Insofar as AI explores designs for possible mental mechanisms, possible mental architectures, and possible minds using those mechanisms and architectures, it is primarily a contribution to deep science, the science of what is possible, in contrast with most empirical psychology which is shallow science, exploring correlations: the science of laws and regularities. In 2007 I attempted, unsuccessfully to generate interest in a multidisciplinary school syllabus combining computing, biology, cognitive science and philosophy.