This article examines decision making in the development context from an information- processing perspective. Drawing on the work of Chenery and Black, three economic and four political strategies are identified. Using an artificial intelligence methodology-the common-sense algorithm-the decision rules for each political strategy and an economic strategy emphasizing self-reliance are modeled. Simulations were run on the strategies. Responses represent ways in which development strategies or images recognize problems and respond to specific actions. Results indicate that the most politically difficult strategy with an economic focus on self-reliance was one that represented an attempt to build and consolidate the leadership of the government. A strategy built on a common ideological creed was the least affected by the specific simulations.
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References
1.
Abelson, R.P. (1973) "The structure of belief systems," in R. C. Schank and K. M. Colby (eds.) Computer Models of Thought and Language. San Francisco: Freeman.
2.
Almond, G. (1971) "Approaches to development causation," in Binder et al. (eds.) Crises and Sequences in Political Development. Princeton, NJ: Princeton Univ. Press.
Bellamy, E. [ed.] (1946) Looking Backward. London: Henricks House .
5.
Black, C.E. (1966) The Politics of Modernization: A Study in Comparative History. New York: Harper & Row.
6.
Bobrow, D.G. and D. Norman (1975) "Some principles of memory schemata," in D. Bobrow and A. Collins (eds.) Representation and Understanding: Studies in Cognitive ScienceNew York: Academic.
7.
Bunge, M. (1959) Causality. Cambridge, MA: Harvard Univ. Press.
8.
Chenery, H. (1979) Structural Change and Development Policy. New York: Oxford Univ. Press.
9.
Davis, R. and J. King (1975) "An overview of production systems." Stanford Artificial Intelligence Laboratory, Stanford, California, AIM-271.
10.
Easton, D. (1953) The Political System: An Inquiry into the State of Political Science. New York: Alfred Knopf.
11.
Feigenbaum, E.A. et al. (1971) "On generality and production systems: a case study involving the DENDRAL program," in Meltzer and Mitchie (eds.) Machine Intelligence. Edinburgh: Edinburgh Univ. Press.
12.
Forrester, J. (1971) World Dynamics. Cambridge, MA : Wright-Allen.
13.
Grinberg, M. and C. Reiger (n.d.) "The mechanism simulator reference manual. University of Maryland, College Park. (mimeo)
Meadows, D.C. and D.H. Meadows et al. (1971) Limits to Growth. New York: Universe.
16.
Mesarovic, M. and E. Pestel (1974) Mankind at the Turning Point. New York: E. P. Dutton.
17.
Miller, R.A. and S. Thorsen ( 1977) "Control concepts in theories of government decision-making ," in J. Gillespie and D. Zinnes (eds.) Mathematical Systems in International Relations. New York: Praeger.
18.
Minsky, M. (1975) "A framework for representing knowledge," in P. H. Winston (ed.) The Psychology of Computer Vision. New York: McGraw-Hill .
19.
Nelson, R. and S. Winter (1973) "Neoclassical versus evolutionary theories of economic growth: critique and prospectus." University of Michigan , Institute for Policy Studies, Ann Arbor.
20.
Newell, A. (1973) "You can't play twenty questions with nature and win," in W. Chase (ed.) Visual Information Processing. New York: Academic.
21.
Nordhaus, W. and J. Tobin (1972) "Is growth obsolete?" in Economic Research: Retrospect and Prospect, Economic Growth. New York: National Bureau of Economic Research.
22.
Nurmi, H. (1974) Causality and Complexity: Some Problems of Causal Analysis in the Social Sciences. Turkey: Turun Yliopista.
23.
Parsons, R. and E. Shills [eds.] (1951) Towards a General Theory of Activity. Cambridge, MA: Harvard University Press.
24.
Phillips, W. and D. McCormick (1979) "A new methodology for the modeling of decision processes in international relations," in Farkus Kuhlmin (ed.) Military Policy Evaluations: Quantitative Applications. Leyden, Netherlands: Sitjhoff.
25.
Rieger, C. (1976a) "The causal representation and simulation of physical mechanisms." TR-495. Department of Computer Science, University of Maryland, College Park.
26.
--- ( 1976b) "Spontaneous computations in cognitive models." TR-459 . Department of Computer Science, University of Maryland , College Park.
27.
--- ( 1975a) "The common sense algorithm as a basis for computer models of human memory, inference, belief systems, and contextual language comprehension." TR-373. Department of Computer Science, University of Maryland , College Park.
28.
——— (1975b) "One system for two tasks." TR-435. Department of Computer Science, University of Maryland, College Park.
29.
Schank, R.C. and K.M. Colby (1973) Computer Models of Thought and Language. San Francisco: Freeman.
30.
Shortleffe, E. et al. (1975) "Computer-based consultations in clinical therapeutics-explanation and rule acquisition capabilities of the MYCIN system ." Computers and Biomedical Research8, 4: 303-320.
31.
Simon, H. (1957) Models of Man. New York: John Wiley.
32.
--- and A. NEWELL (1972) Human Problem Solving. Englewood Cliffs, NJ: Prentice-Hall.
33.
Torneboh M.H. (1969) Science as innovative system." Institute for Metascience, University of Gothenberg. (mimeo)
34.
Wells, H.G. (1902) Anticipation. London: Chapman.
35.
Wold, H. (1970) "Challenge and response," in P. Londbloom (ed.) Theory and Methods in Behavioral Science. Stockholm: University of Stockholm.
36.
——— (1969) "Mergers of economics and philosophy of science ." Synthese (December).
37.
——— (1968) "Ends and means of scientific methods with a special regard to the social sciences," in B. Lindskog (ed.) Universitetet och forskninge. Uppsala: Uppsala University.
