An axiomatic treatment of three qualitative decision criteria

The need for computationally efficient decision-making techniques together with the desire to simplify the processes of knowledge acquisition and agent specification have led various researchers in artificial intelligence to examine qualitative decision tools. However, the adequacy of such tools is not clear. This paper investigates the foundations of maximin, minmax regret, and competitive ratio, three central qualitative decision criteria, by characterizing those behaviors that could result from their use. This characterizaton provides two important insights: (1)under what conditions can we employ an agent model based on these basic qualitative decision criteria, and (2) how “rational” are these decision procedures. For the competitive ratio criterion in particular, this latter issue is of central importance to our understanding of current work on on-line algorithms. Our main result is a constructive representation theorem that uses two choice axioms to characterize maximin, minmax regret, and competitive ratio.

[1]  Ronald A. Howard,et al.  Dynamic Programming and Markov Processes , 1960 .

[2]  Ronald Fagin,et al.  Reasoning about knowledge , 1995 .

[3]  David M. Kreps Notes On The Theory Of Choice , 1988 .

[4]  I. Gilboa,et al.  Case-Based Decision Theory , 1995 .

[5]  Peter Gärdenfors,et al.  Belief Revision: Contents , 1992 .

[6]  Ronen I. Brafman,et al.  On Decision-Theoretic Foundations for Defaults , 1995, IJCAI.

[7]  Abraham Wald,et al.  Statistical Decision Functions , 1951 .

[8]  J. Doyle,et al.  Representing Preferences as Ceteris Paribus Comparatives , 1994 .

[9]  Joseph Y. Halpern Reasoning About Knowledge: An Overview , 1986, TARK.

[10]  Kenneth D. Forbus Qualitative Process Theory , 1984, Artif. Intell..

[11]  Joseph Y. Halpern,et al.  Knowledge and common knowledge in a distributed environment , 1984, JACM.

[12]  Daniel Lehmann,et al.  Generalized Qualitative Probability: Savage revisited , 1996, UAI.

[13]  Solomon Eyal Shimony,et al.  Finding MAPs for Belief Networks is NP-Hard , 1994, Artif. Intell..

[14]  Allan Borodin,et al.  Online computation and competitive analysis , 1998 .

[15]  James A. Hendler,et al.  Readings in Planning , 1994 .

[16]  Moisés Goldszmidt,et al.  On the Relation between Kappa Calculus and Probabilistic Reasoning , 1994, UAI.

[17]  Christos H. Papadimitriou,et al.  Games against nature , 1983, 24th Annual Symposium on Foundations of Computer Science (sfcs 1983).

[18]  John F. Sowa,et al.  Knowledge Representation and Reasoning , 2000 .

[19]  F. J. Anscombe,et al.  A Definition of Subjective Probability , 1963 .

[20]  Judea Pearl,et al.  Specification and Evaluation of Preferences Under Uncertainty , 1994, KR.

[21]  L. J. Savage,et al.  The Foundations of Statistics , 1955 .

[22]  Mihalis Yannakakis,et al.  Shortest Paths Without a Map , 1989, Theor. Comput. Sci..

[23]  Matthew L. Ginsberg,et al.  Readings in Nonmonotonic Reasoning , 1987, AAAI 1987.

[24]  Ronen I. Brafman,et al.  Belief Ascription and Mental-Level Modelling , 1994, KR.

[25]  S. Vajda,et al.  GAMES AND DECISIONS; INTRODUCTION AND CRITICAL SURVEY. , 1958 .

[26]  Joseph Y. Halpern,et al.  A Knowledge-Based Framework for Belief change, Part I: Foundations , 1994, TARK.

[27]  Ronen I. Brafman,et al.  Modeling Agents as Qualitative Decision Makers , 1997, Artif. Intell..

[28]  Didier Dubois,et al.  Possibility Theory as a Basis for Qualitative Decision Theory , 1995, IJCAI.

[29]  Didier Dubois,et al.  Decision-theoretic foundations of qualitative possibility theory , 2001, Eur. J. Oper. Res..

[30]  Jon Doyle,et al.  Constructive belief and rational representation , 1989, Comput. Intell..

[31]  Jon Doyle,et al.  Impediments to Universal Preference-Based Default Theories , 1989, KR.

[32]  Gregory F. Cooper,et al.  The Computational Complexity of Probabilistic Inference Using Bayesian Belief Networks , 1990, Artif. Intell..

[33]  L. Zadeh Fuzzy sets as a basis for a theory of possibility , 1999 .

[34]  E. Rowland Theory of Games and Economic Behavior , 1946, Nature.

[35]  I. Gilboa,et al.  Maxmin Expected Utility with Non-Unique Prior , 1989 .

[36]  Peter C. Fishburn,et al.  Nonlinear preference and utility theory , 1988 .

[37]  Judea Pearl,et al.  Qualitative Decision Theory , 1994, AAAI.

[38]  Eddie Dekel,et al.  Lexicographic Probabilities and Equilibrium Refinements , 1991 .

[39]  Craig Boutilier,et al.  Toward a Logic for Qualitative Decision Theory , 1994, KR.

[40]  Yoav Shoham,et al.  Knowledge, Certainty, Belief, and Conditionalisation (Abbreviated Version) , 1994, KR.

[41]  Sergiu Hart,et al.  A Neo2 bayesian foundation of the maxmin value for two-person zero-sum games , 1994 .

[42]  Eddie Dekel,et al.  Lexicographic Probabilities and Choice Under Uncertainty , 1991 .

[43]  Louis J. Hoebel,et al.  Book review: Readings in Planning Edited by James Allen, James Hendler, and Austin Tate (Morgan Kaufmann, San Mateo, CA, 1990) , 1991, SGAR.