linear time and space: A structured presentation. Internal Report B 7616, Istituto di Elaborazione della Informazione, Pisa, Italy. Martelli, A.
and Montanari, U. (1978). Optimizing decision trees through
heuristically guided search. Communications of the
(1988). Probabilistic Reasoning in Intelligent Systems: Networks of
Plausible Inference. Morgan Kaufmann, San Mateo, California.
Pednault, E. P. D. (1986). Formulating multiagent, dynamic-world
problems in the classical planning framework. In Georgeff, M.
in Intelligent Vehicle Highway Systems, pages 30-36, Washington, D.C.
Kirkpatrick, S., Gelatt, C. D., and Vecchi, M. P. (1983). Optimization by
simulated annealing. Science, 220:671-680. Kirkpatrick, S. and Selman,
B. (1994). Critical behavior in the sati
Breach, New York. Michie, D. (1986). Current developments in expert
systems. In Proc. 2nd Australian Conference on Applications of Expert
Systems, pages 163-182, Sydney, Australia. Michie, D. and Chambers,
R. A. (1968). BOXES: An experiment in adaptive co
for medical decision analysis. International Journal of Technology
Assessment in Health Care, 5:357-370. Howard, R. A. and Matheson, J.
E. (1984). Influence diagrams. In Howard, R. A. and Matheson, J.E.,
editors, Readings on the Principles and Application
question. Will intelligent automation give people more fulfilling work
and more relaxing leisure time? Or will the pressures of competing in a
nanosecond-paced world lead to more stress? Will children gain from
instant access to intelligent tutors, multim
rather than speed of computation. Again, the bounded optimal program
for the automaton is rather messy, but its existence and properties are
what counts. 848 Chapter 27. AI: Present and Future 27.3 WHAT IF WE
Do SUCCEED?_ _ In David Lodge's Small World, ,
program has been granted legal status as an individual for the purposes
of financial transactions; at present, it seems unreasonable to do so.
Programs are also not considered to be "drivers" for the purposes of
enforcing traffic regulations on real highw
machines will achieve high levels of intelligent behavior and will
communicate with humans as apparent equals, then these questions are
unavoidable. Should (or will) intelligent machines have rights? How
should intelligent machines interact with humans? W
Press, Chicago, Illinois, second edition. Jelinek, F. (1976). Continuous
speech recognition by statistical methods. Proceedings of the IEEE,
64(4):532-556. Jelinek, F. (1990). Self-organizing language modeling
for speech recognition. In Waibel, A. and Eee
technology can be misused to the detriment of humanity. Arguments
over the desirability of a given technology must weigh the benefits and
risks, and put the onus on researchers to ensure that policy makers and
the public have the best possible information
function of the size of the input. We will call this T(n). With the simpler
measure, we have T(n) = 2n + 2 for our example. If all programs were as
simple as SUMMATION, analysis of algorithms would be a trivial field.
But two problems make it more complic
35(3):287- 310. McAllester, D. A. (1989). Ontic: A Knowledge
Representation System for Mathematics. MIT Press, Cambridge,
Massachusetts. McAllester, D. A. and Givan, R. (1992). Natural
language syntax and first-order inference. Artificial Intelligence,
Association for Computing Machinery, 10(3):137. Jackson, P. (1986).
Introduction to Expert Systems. Addison-Wesley, Reading,
Massachusetts. Jacobs, P. and Rau, E. (1990). Scisor: A system for
extracting information from on-line news. Communications of the
2:397-404. Johnson-Laird, P. N. (1988). The Computer and the Mind:
An Introduction to Cognitive Science. Harvard University Press,
Cambridge, Massachusetts. Johnston, M. D. and Adorf, H.-M. (1992).
Scheduling with neural networks: the case of the Hubble s
defection also occurs when the game has a finite number of rounds.
(This can easily be proved by working backwards from the last round.)
Recently, however, there has been a shift from consideration of optimal
decisions in games to a consideration of optim
at Los Angeles. Kirn, J. H. and Pearl, J. (1983). A computational model
for combined causal and diagnostic reasoning in inference systems. In
Proceedings of the Eighth International Joint Conference on Artificial
Intelligence (IJCAI-83), pages 190-193, Ka
Foundations of Cyclopean Perception. University of Chicago Press,
Chicago, Illinois. Kaelbling, L. P. (1990). Learning functions in kDNF
from reinforcement. In Machine Learning: Proceedings of the Seventh
International Conference, pages 162-169, Austin, T
of agents who make their decisions simultaneously, without knowledge
of the decisions of the other agents. The Prisoner's Dilemma is a famous
example, in which each of two crime suspects can "collaborate" (refuse
to implicate his or her partner) or "defec
analysis. In Eklundh, J.-O., editor, Proceedings of the Third European
Conf. on Computer Vision, pages 353-364, Stockholm.
SpringerVerlag.Published as Lecture Notes in Computer Science 800.
Manin, Y. I. (1977). A Course in Mathematical Logic. Springer-Ver
fast computing machines. Journal of Chemical Physics, 21:1087-1091.
Mezard, M. and Nadal, J.-P. (1989). Learning in feedforward layered
networks: The tiling algorithm. Journal of Physics, 22:2191-2204.
Michalski, R. S., Carbonell, J. G., and Mitchell, T.
patient but as influencing the physician's behavior. If expert systems
become reliably more accurate than human diagnosticians, doctors may
be legally liable if they fail to use the recommendations of an expert
system. Similar issues are beginning to aris
United States, it is hardly surprising that legal liability needs to be
discussed. When a physician relies on the judgment of a medical expert
system for a diagnosis, who is at fault if the diagnosis is wrong?
Fortunately, due in part to the growing influ
editor, The Psychology of Computer Vision, pages 211-277.
McGrawHill, New York.Originally appeared as an MIT Artificial
Intelligence Laboratory memo; the present version is abridged, but is the
most widely cited. Another, later abridged version appeared i
Press. Kalman, R. E. (1960). A new approach to linear filtering and
prediction problems. Journal of Basic Engineering, pages 35^6.
Kambhampati, S. and Nau, D. S. (1993). On the nature and role of
modal truth criteria in planning. Technical Report ISR-TR-9
Metatheory of Standard First-Order Logic. University of California
Press, Berkeley and Eos Angeles. Hunter, E. and States, D. J. (1992).
Bayesian classification of protein structure. IEEE Expert, 7(4):67- 75.
Huttenlocher, D. P. and Ullman, S. (1990). Rec
of a sequence of numbers: function S\JMMAi:iON(sequence) returns a
number sum 0 for i 1 to LENGTH(sequence) .turn sum +
sequence[i] end return sum The first step in the analysis is to abstract
over the input, to find some parameter or parameters that char
of Symbolic Logic, 16:14-21. Horn, B. K. P. (1970). Shape from
shading: a method for obtaining the shape of a smooth opaque object
from one view. Technical Report 232, MIT Artificial Intelligence
Laboratory, Cambridge, Massachusetts. Horn, B. K. P. (1986)
single two-dimensional images. Artificial Intelligence, 31:355-395.
Lowenheim, L. (1915). Uber moglichkeiten im Relativkalkiil.
Mathematische Annalen, 76:447- 470. Reprinted in English translation
in van Heijenoort (1967). Lowerre, B. T. and Reddy, R. (19
Strategies for Complex Problem Solving. Benjamin/Cummings,
Redwood City, California, second edition. Mackworth, A. K. (1973).
Interpreting pictures of polyhedral scenes. Artificial Intelligence, 4:121137. Maes, P., Darrell, T., Blumberg, B., and Pentland,