Technology
Learning logic
Technical report TR-47, Center for Computational Research in Economics and Management Science, Massachusetts Institute of Technology.
Implementation of logical query languages for databases
ACM Transactions on Database Systems, 10 (3), 289-321.
Reasoning about preference models
Technical report MIT/LCS/TR-340, Laboratory for Computer Science, MIT.
Probabilistic interpretation for MYCIN's certainty factors
Proc. Workshop on Uncertainty and Probability in Artificial Intelligence, Los Angeles, CA, pages 9-20. Association for Uncertainty in Artificial Intelligence, Mountain View, CA, August 1985.
Analogy
Informal note INCSLI-85-4, Center for the Study of Language and Information. Not available online. Alternative: Davies, Todd R.; Russell, Stuart J. A Logical Approach to Reasoning by Analogy. SRI International Technical Note 385, July 1987. Determination, uniformity, and relevance: Normative criteria for generalization and reasoning by analogy. In D. H. Helman (ed.), Analogical Reasoning, 227-250. Kluwer Academic Publishers, 1988.
Review of A Practical Guide to Designing Expert Systems
Review of A Practical Guide to Designing Expert Systems
The Professor's Challenge
The AI field needs major breakthroughs in its thinking to achieve continuous, sensory-gathered, machine learning from the environment on unlimited subjects. The way motivate such dramatic progress is to articulate and endorse research goals for machine behavior so ambitious that limited-domain, problemsolving knowledge representation methods are disqualified at the outset, thus forcing ourselves to produce valuable new "thoughtware." After exploring why the tendency to associate intelligence with problem-solving may be a mental roadblock to further progress in AI science, some preliminary thinking tools are introduced more suitable for sensory learning machine research. These include lifelong sensorimotor data streams, representation as a symbolic recording process, knowledge transmission, and the totality of knowledge.