Report Number: CS-TR-70-147 Institution: Stanford University, Department of Computer Science Title: Pitfalls in computation, or why a math book isn't enough Author: Forsythe, George E. Date: January 1970 Abstract: The floating-point number system is contrasted with the real numbers. The author then illustrates the variety of computational pitfalls a person can fall into who merely translates information gained from pure mathematics courses into computer programs. Examples include summing a Taylor series, solving a quadratic equation, solving linear algebraic systems, solving ordinary and partial differential equations, and finding polynomial zeros. It is concluded that mathematics courses should be taught with a greater awareness of automatic computation. ftp://reports.stanford.edu/pub/cstr/reports/cs/tr/70/147/CS-TR-70-147.pdf Report Number: CS-TR-70-156 Institution: Stanford University, Department of Computer Science Title: On a model for computing round-off error of a sum Author: Dantzig, George B. Date: March 1970 Abstract: No abstract available. ftp://reports.stanford.edu/pub/cstr/reports/cs/tr/70/156/CS-TR-70-156.pdf Report Number: CS-TR-70-171 Institution: Stanford University, Department of Computer Science Title: A survey of models for parallel computing Author: Bredt, Thomas H. Date: August 1970 Abstract: The work of Adams, Karp and Miller, Luconi, and Rodriguez on formal models for parallel computations and computer systems is reviewed. A general definition of a parallel schema is given so that the similarities and differences of the models can be discussed. Primary emphasis is on the control structures used to achieve parallel operation and on properties of the models such as determinacy and equivalence. Decidable and undecidable properties are summarized. ftp://reports.stanford.edu/pub/cstr/reports/cs/tr/70/171/CS-TR-70-171.pdf Report Number: CS-TR-71-247 Institution: Stanford University, Department of Computer Science Title: One small head -- some remarks on the use of 'model' in linguistics Author: Wilks, Yorick A. Date: December 1971 Abstract: I argue that the present situation in formal linguistics, where much new work is presented as being a "model of the brain", or of "human language behavior", is an undesirable one. My reason for this judgement is not the conservative (Braithwaitian) one that the entities in question are not really models but theories. It is rather that they are called models because they cannot be theories of the brain at the present stage of brain research, and hence that the use of "model" in this context is not so much aspirational as resigned about our total ignorance of how the brain stores and processes linguistic information. The reason such explanatory entities cannot be theories is that this ignorance precludes any "semantic ascent" up the theory; i.e., interpreting the items of the theory in terms of observables. And the brain items, whatever they may be, are not, as Chomsky has sometimes claimed, in the same position as the "occult entities" of Physics like Gravitation; for the brain items are not theoretically unreachable, merely unreached. I then examine two possible alternate views of what linguistic theories should be proffered as theories of: theories of sets of sentences, and theories of a particular class of algorithms. I argue for a form of the latter view, and that its acceptance would also have the effect of making Computational Linguistics a central part of Linguistics, rather than the poor relation it is now. I examine a distinction among "linguistic models" proposed recently by Mey, who was also arguing for the self-sufficiency of Computational Linguistics, though as a "theory of performance". I argue that his distinction is a bad one, partly for the reasons developed above and partly because he attempts to tie it to Chomsky's inscrutable competence-performance distinction. I conclude that the independence and self-sufficiency of Computational Linguistics are better supported by the arguments of this paper. CS-TR-71-247 Title: The frame problem and related problems in artificial intelligence Author: Hayes, Patrick J. ftp://reports.stanford.edu/pub/cstr/reports/cs/tr/71/242/CS-TR-71-242.pdf Report Number: CS-TR-71-242 Institution: Stanford University, Department of Computer Science Date: November 1971 Abstract: The frame problem arises in considering the logical structure of a robot's beliefs. It has been known for some years, but only recently has much progress been made. The problem is described and discussed. Various suggested methods for its solution are outlined, and described in a uniform notation. Finally, brief consideration is given to the problem of adjusting a belief system in the face of evidence which contradicts beliefs. It is shown that a variation on the situation notation of (McCarthy and Hayes, 1969) permits an elegant approach, and relates this problem to the frame problem.