Akman, Varol


Steps toward Formalizing Context

AI Magazine

The importance of contextual reasoning is emphasized by various researchers in AI. (A partial list includes John McCarthy and his group, R. V. Guha, Yoav Shoham, Giuseppe Attardi and Maria Simi, and Fausto Giunchiglia and his group.) Here, we survey the problem of formalizing context and explore what is needed for an acceptable account of this abstract notion.


Steps toward Formalizing Context

AI Magazine

The importance of contextual reasoning is emphasized by various researchers in AI. (A partial list includes John McCarthy and his group, R. V. Guha, Yoav Shoham, Giuseppe Attardi and Maria Simi, and Fausto Giunchiglia and his group.) Here, we survey the problem of formalizing context and explore what is needed for an acceptable account of this abstract notion.


Review of Actors: A Model of Concurrent Computation in Distributed Systems

AI Magazine

Gul A. Agha's "Actors: A Model of Concurrent Computation in Distributed Systems (The MIT Press, Cambridge, Mass., 1987, 144 pages, $25.00, ISBN 0-262-01092-5) is part of the MIT Press Series in Artificial Intelligence. This volume is edited by Patrick Winston, Michael Brady, and Daniel Bobrow.


No Reliance Can Be Placed on Appearance: A Response to Kuipers (Letter to the Editor)

AI Magazine

In a letter to the editor (AI Magazine, Winter 1989), Benjamin Kuipers criticizes various points made in an earlier paper of ours (Akman and ten Hagen 1989). First, a side (nonetheless important) remark: Although Kuipers asserts that he distributes QSIM to interested researchers, our experience has been otherwise. Akman has tried twice to obtain QSIM, without success. Although Kuipers promised to deliver a copy -- QSIM was under revision at the time of Akman's request (this being as early as winter 1988) -- the program was never sent. So much for the availability of QSIM. . . . Kuipers' letter is full of sweeping generalizations that are so much against the nature of scientific enterprise. We should also add that we are disappointed to see Kuipers employing universal truths and unarguable facts such as ". . . if you build the wrong model, the predictions derived from that model are likely to be wrong" or ". . . guarantees of mathematical validity [are] necessary for any science" as his main cheval de bataille. In the following we'll point out, one by one, the weaknesses of QSIM. Our task will be easy since we shall merely reproduce, almost verbatim, Kuipers' own sentences (Kuipers 1986) and, additionally, Janowski's (1987) views. (The latter reference gives an excellent review of QSIM's disadvantages.) Then, we'll let the reader judge.


The Power of Physical Representations

AI Magazine

Commonsense reasoning about the physical world, as exemplified by "Iron sinks in water" or "If a ball is dropped it gains speed," will be indispensable in future programs. We argue that to make such predictions (namely, envisioning), programs should use abstract entities (such as the gravitational field), principles (such as the principle of superposition), and laws (such as the conservation of energy) of physics for representation and reasoning. These arguments are in accord with a recent study in physics instruction where expert problem solving is related to the construction of physical representations that contain fictitious, imagined entities such as forces and momenta (Larkin 1983). We give several examples showing the power of physical representations.


The Power of Physical Representations

AI Magazine

Commonsense reasoning about the physical world, as exemplified by "Iron sinks in water" or "If a ball is dropped it gains speed," will be indispensable in future programs. We argue that to make such predictions (namely, envisioning), programs should use abstract entities (such as the gravitational field), principles (such as the principle of superposition), and laws (such as the conservation of energy) of physics for representation and reasoning. These arguments are in accord with a recent study in physics instruction where expert problem solving is related to the construction of physical representations that contain fictitious, imagined entities such as forces and momenta (Larkin 1983). We give several examples showing the power of physical representations.


Letters to the Editor

AI Magazine

Thanks from Jack and Janet Mostow for causing them to meet at AAAI'87 and subsequently marry; a correction to Jordan Pollack's affiliation; a correction to the winter 1988 wording of his report on Workshop on Theoretical Issues in Conceptual Information Processing; an addendum to the Slagle and Wick article in 9, 4: A Method for Evaluating Candidate Expert System Applications, citing Bruno Franck, and comments on Intelligent Computer-Aided Engineering by Kenneth D. Forbus in vol 9, no 3.


Letters to the Editor

AI Magazine

Thanks from Jack and Janet Mostow for causing them to meet at AAAI'87 and subsequently marry; a correction to Jordan Pollack's affiliation; a correction to the winter 1988 wording of his report on Workshop on Theoretical Issues in Conceptual Information Processing; an addendum to the Slagle and Wick article in 9, 4: A Method for Evaluating Candidate Expert System Applications, citing Bruno Franck, and comments on Intelligent Computer-Aided Engineering by Kenneth D. Forbus in vol 9, no 3.