Abstract
Counterexamples are constructed for classical decision theory, turning on the fact that actions must often be chosen in groups rather than individually, i.e., the objects of rational choice are plans. It is argued that there is no way to define optimality for plans that makes the finding of optimal plans the desideratum of rational decision-making. An alternative called “locally global planning” is proposed as a replacement for classical decision theory. Decision-making becomes a non-terminating process without a precise target rather than a terminating search for an optimal solution.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Blythe, J. and M. Veloso (1997), Analogical replay for efficient conditional planning, AAAI9.
C. Boutelier D. Thomas H. Steve (1999) ArticleTitleDecision theoretic planning: Structural assumptions and computational leverage Journal of Al Research 11 1–94
C. Cherniak (1986) Minimal Rationality MIT Press Cambridge
A. Gibbard W. Harper (1978) Counterfactuals and two kinds of expected utility C. A. Hooker J. J. Leach E. F. McClennen (Eds) Foundation and Applications of Decision Theory Reidel Dordrecht 125–162
Haddawy, P. and Hanks, S. (1990), Issues in decision-theoretic planning: Symbolic goals and numeric utilities, Proceedings of the DARPA Workshop on Innovative Approaches to Planning, Scheduling, and Control 48–58.
D. Lewis (1981) ArticleTitleCausal decision theory Australasian Journal of Philosophy 59 5–30
Ngo, L., Haddawy, P. and Nguyen, H. (1998), A modular structured approach to conditional decision-theoretic Planning, AIPS’98 111–118.
Onder, N. and Pollack, M. (1997), Contingency selection in plan generation, ECP97.
Onder, N. and Pollack, M. (1999), Conditional, probabilistic planning: A unifying algorithm and effective search control mechanisms, AAAI 99.
Onder, N., Pollack, M. and Horty J. (1998), A unifying algorithm for conditional, probabilistic planning, AIPS1998 Workshop on Integrating Planning, Scheduling, and Execution in Dynamic and Uncertain Environments.
J. Pollock (1990) Nomic Probability and the Foundations of Induction Oxford University Press Oxford
J. Pollock (1992) ArticleTitleNew foundations for practical reasoning Minds and Machines 2 113–144
J. Pollock (1999) ArticleTitleThe logical foundations of goal-regression planning in autonomous agents Artificial Intelligence 106 267–335
J. Pollock (2001) ArticleTitleEvaluative cognition Nous 35 325–364
J. Pollock (2002) ArticleTitleCasual probability Synthese 132 143–185
J. Pollock (2003) ArticleTitleRational choice and action omnipotence Philosophical Review 111 1–23
Pollock, J. (2005), Thinking about Acting: Logical Foundations for Rational Decision-making. http://www.u.arizona.edu/~pollock/.
L. Savage (1954) The Foundations of Statistics Dover New York
H. Simon (1955) ArticleTitleA behavioral model of rational choice Quarterly Journal of Economics 59 99–118
B. Skyrms (1980) Causal Necessity Yale University Press New Haven
B. Skyrms (1982) ArticleTitleCausal decision theory Journal of Philosophy 79 695–711
B. Skyrms (1984) Pragmatics and Empiricism Yale University Press New Haven
Sobel, H. (1978), Probability, Chance, and Choice: A Theory of Rational Agency, unpublished paper presented at a workshop on Pragmatism and Conditionals at the University of Western Ontario, May, 1978.
D. Weld (1999) ArticleTitleRecent advances in AI planning AI Magazine 20 55–68
Williamson, M. and Hanks, S. (1994), Beyond symbolic goals: A step toward utility-directed planning, AAAI Spring Symposium on Decision-Theoretic Planning 272–278.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Pollock, J.L. Plans And Decisions. Theor Decis 57, 79–107 (2004). https://doi.org/10.1007/s11238-004-7318-7
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11238-004-7318-7