Easy and optimal queries to reduce set uncertainty

In this paper, we address the problem of optimally querying a single expert to reduce set (interval) uncertainty. We propose optimal querying strategies for two particular query formats (local bound and pairwise comparisons) based on two main selection criteria (the minimax and the Bayesian rules). We study the computational aspects of the optimal solution in the general case and for the specific functions of practical interest (monotonic and multi-linear). The use of the proposed approach is illustrated through numerical simulations on a common estimation problem in reliability analysis.

[1]  Stephen Warshall,et al.  A Theorem on Boolean Matrices , 1962, JACM.

[2]  Craig Boutilier,et al.  Efficient Vote Elicitation under Candidate Uncertainty , 2013, IJCAI.

[3]  Arthur P. Dempster,et al.  Upper and Lower Probabilities Induced by a Multivalued Mapping , 1967, Classic Works of the Dempster-Shafer Theory of Belief Functions.

[4]  Christophe Labreuche,et al.  On the extension of pseudo-Boolean functions for the aggregation of interacting criteria , 2003, Eur. J. Oper. Res..

[5]  Mohamed Sallak,et al.  Extended Component Importance Measures Considering Aleatory and Epistemic Uncertainties , 2013, IEEE Transactions on Reliability.

[6]  R. F. Drenick,et al.  Multilinear programming: Duality theories , 1992 .

[7]  Martin E. Dyer,et al.  On the Complexity of Computing the Volume of a Polyhedron , 1988, SIAM J. Comput..

[8]  Eyke Hüllermeier,et al.  Learning Monotone Nonlinear Models Using the Choquet Integral , 2011, ECML/PKDD.

[9]  Roger M. Cooke,et al.  Quantifying scientific uncertainty from expert judgement elicitation , 2013 .

[10]  Frank P. A. Coolen,et al.  Nonparametric predictive reliability of series of voting systems , 2013, Eur. J. Oper. Res..

[12]  Roger M. Cooke,et al.  Expert judgment in maintenance optimization , 1992 .

[13]  Salvatore Greco,et al.  Ordinal regression revisited: Multiple criteria ranking using a set of additive value functions , 2008, Eur. J. Oper. Res..

[14]  G. Owen Multilinear Extensions of Games , 1972 .

[15]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.

[16]  Hanif D. Sherali,et al.  CONVEX ENVELOPES OF MULTILINEAR FUNCTIONS OVER A UNIT HYPERCUBE AND OVER SPECIAL DISCRETE SETS , 1997 .

[17]  Patrice Perny,et al.  Incremental Elicitation of Choquet Capacities for Multicriteria Decision Making , 2014, ECAI.

[18]  Emanuele Borgonovo,et al.  Elicitation of multiattribute value functions through high dimensional model representations: Monotonicity and interactions , 2015, Eur. J. Oper. Res..

[19]  Emad El-Neweihi,et al.  Measures of component importance in reliability theory , 1995, Comput. Oper. Res..

[20]  M. Yannakakis Expressing combinatorial optimization problems by linear programs , 1991, Symposium on the Theory of Computing.

[21]  Ariel D. Procaccia,et al.  Strategyproof Classification with Shared Inputs , 2009, IJCAI.

[22]  Jean-Luc Marichal Structure Functions and Minimal Path Sets , 2016, IEEE Transactions on Reliability.

[23]  A. Curtis,et al.  Optimal elicitation of probabilistic information from experts , 2004, Geological Society, London, Special Publications.

[24]  Sébastien Destercke,et al.  Optimal expert elicitation to reduce interval uncertainty , 2015, UAI.

[25]  L. Khachiyan Complexity of Polytope Volume Computation , 1993 .

[26]  David Cohn,et al.  Active Learning , 2010, Encyclopedia of Machine Learning.

[27]  Garth P. McCormick,et al.  Computability of global solutions to factorable nonconvex programs: Part I — Convex underestimating problems , 1976, Math. Program..

[28]  Anatoliy D. Rikun,et al.  A Convex Envelope Formula for Multilinear Functions , 1997, J. Glob. Optim..

[29]  G. Brightwell,et al.  Counting linear extensions , 1991 .

[30]  Enrico Zio,et al.  A method for ranking components importance in presence of epistemic uncertainties , 2009 .

[31]  Craig Boutilier,et al.  Constraint-based optimization and utility elicitation using the minimax decision criterion , 2006, Artif. Intell..

[32]  Jaime G. Carbonell,et al.  Active Learning-Based Elicitation for Semi-Supervised Word Alignment , 2010, ACL.

[33]  Craig Boutilier,et al.  A POMDP formulation of preference elicitation problems , 2002, AAAI/IAAI.

[34]  Yves Crama,et al.  Boolean methods in operations research and related areas , 2011 .

[35]  B. J. Leon,et al.  A New Algorithm for Symbolic System Reliability Analysis , 1976, IEEE Transactions on Reliability.

[36]  Didier Dubois,et al.  Gradual Numbers and Their Application to Fuzzy Interval Analysis , 2008, IEEE Transactions on Fuzzy Systems.

[37]  Paolo Viappiani,et al.  Robust Optimization of Recommendation Sets with the Maximin Utility Criterion , 2013, ADT.

[38]  N. Singpurwalla,et al.  Expert Opinion in Reliability , 1993 .

[39]  S. Ferson,et al.  Different methods are needed to propagate ignorance and variability , 1996 .

[40]  Cosimo Laneve,et al.  The Interval Analysis of Multilinear Expressions , 2010, Electron. Notes Theor. Comput. Sci..

[41]  H. W. Kalfsbeek,et al.  Elicitation, assessment, and pooling of expert judgments using possibility theory , 1995, IEEE Trans. Fuzzy Syst..

[42]  Valerii V. Fedorov,et al.  Optimal experimental design , 2010 .

[43]  A. Wald Statistical Decision Functions Which Minimize the Maximum Risk , 1945 .