Collaborating Authors

A theory of approximate reasoning


In J. E. Hayes, D. Michie, and L. I. Mikulich (Eds.), Machine Intelligence 9. Chichester, England: Ellis Horwood Ltd., 149-195

Interactive transfer of expertise: Acquisition of new inference rules


Summary of Ph.D. dissertation, Computer Science Dept., Stanford University (1979)."TEIRESIAS is a program designed to provide assistance on the task of building knowledge-based systems. It facilitates the interactive transfer of knowledge from a human expert to the system, in a high level dialog conducted in a restricted subset of natural language. This paper explores an example of TEIRESIAS in operation and demonstrates how it guides the acquisition of new inference rules. The concept of meta-level knowledge is described and illustrations given of its utility in knowledge acquisition and its contribution to the more general issues of creating an intelligent program."Also in:Readings in Artificial Intelligence, ed. Webber, Bonnie Lynn and Nils J. Nilsson, Palo Alto, CA: Tioga Publishing Co., 1981.Orig. in IJCAI-77, vol.1, pp. 321 ff. Preprint in Stanford HPP Report #HPP-77-9.See also: Artificial Intelligence, 12[#2]:409-427. Readings in Artificial Intelligence, ed. Webber, Bonnie Lynn and Nils J. Nilsson, Palo Alto, CA: Tioga Publishing Co., 1981

Modelling Distributed Systems


Distributed systems are multi-processor information processing systems whichdo not rely on the central shared memory for communication. The importanceof distributed systems has been growing with the advent of "computer networks"of a wide spectrum: networks of geographically distributed computers at one end,and tightly coupled systems built with a large number of inexpensive physicalprocessors at the other end. Both kinds of distributed system are made availableby the rapid progress in the technology of large-scale integrated circuits. Yetlittle has been done in the research on semantics and programming methodologiesfor distributed information processing systems.Our main research goal is to understand and describe the behaviour of suchdistributed systems in seeking the maximum benefit of employing multi-processorcomputation schemata.Hayes, J.E., D. Michie, and L. I. Mikulich (Eds.), Machine Intelligence 9, Ellis Horwood.

Machines Who Think


A fascinating "must-read" that traces the quest for artificial intelligence back to ancient times, and then proceeds though various current topics with readable explanations and lively interview excerpts. Updated in 2004.] '"This twenty-fifth anniversary edition [of 2004] will contain a lengthy afterword.... It will also have two time lines, one where the history of AI is narrowly construed, and another where AI is cast into a far larger context of human endeavor...."See her AI FAQ Collection. Questions include:How long has the human race dreamed about thinking machines?What does it mean that a machine beat Garry Kasparov, the world's chess champion?Artificial intelligence - is it real?What so-called smart computers do -- is that really thinking?But doesn't that mean our own machines will replace us?Shouldn't we just say no to intelligent machines? Aren't the risks too scary?What's ahead as AI succeeds even more?Original: W. H. Freeman and Co., San Francisco; 25th Anniversary Edition: Natick, MA: A K Peters, Ltd., 2004