Guarantees for the success frequency of an algorithm for finding Dodgson-election winners

Abstract In the year 1876 the mathematician Charles Dodgson, who wrote fiction under the now more famous name of Lewis Carroll, devised a beautiful voting system that has long fascinated political scientists. However, determining the winner of a Dodgson election is known to be complete for the Θ2p level of the polynomial hierarchy. This implies that unless P=NP no polynomial-time solution to this problem exists, and unless the polynomial hierarchy collapses to NP the problem is not even in NP. Nonetheless, we prove that when the number of voters is much greater than the number of candidates—although the number of voters may still be polynomial in the number of candidates—a simple greedy algorithm very frequently finds the Dodgson winners in such a way that it “knows” that it has found them, and furthermore the algorithm never incorrectly declares a nonwinner to be a winner.

[1]  Jörg Rothe,et al.  Exact Complexity of the Winner Problem for Young Elections , 2001, Theory of Computing Systems.

[2]  Andrew V. Goldberg,et al.  On finding the exact solution of a zero-one knapsack problem , 1984, STOC '84.

[3]  Lena Chang,et al.  Canonical Coin Changing and Greedy Solutions , 1976, JACM.

[4]  Rodney G. Downey,et al.  Parameterized complexity for the skeptic , 2003, 18th IEEE Annual Conference on Computational Complexity, 2003. Proceedings..

[5]  Klaus W. Wagner,et al.  Bounded Query Classes , 1990, SIAM J. Comput..

[6]  Jörg Rothe,et al.  On Approximating Optimal Weighted Lobbying, and Frequency of Correctness Versus Average-Case Polynomial Time , 2007, FCT.

[7]  Jim Kadin The Polynomial Time Hierarchy Collapses if the Boolean Hierarchy Collapses , 1988, SIAM J. Comput..

[8]  Russell Impagliazzo,et al.  A personal view of average-case complexity , 1995, Proceedings of Structure in Complexity Theory. Tenth Annual IEEE Conference.

[9]  Geoffrey Pritchard,et al.  Approximability of Dodgson’s rule , 2008, Soc. Choice Welf..

[10]  Giorgio Ausiello,et al.  Theoretical Computer Science Approximate Solution of Np Optimization Problems * , 2022 .

[11]  Maurizio Talamo,et al.  A New Probabilistic Model for the Study of Algorithmic Properties of Random Graph Problems , 1983, FCT.

[12]  Edith Hemaspaandra,et al.  The complexity of Kemeny elections , 2005, Theor. Comput. Sci..

[13]  Edith Hemaspaandra,et al.  Computational Politics: Electoral Systems , 2000, MFCS.

[14]  C. Papadimitriou,et al.  Two remarks on the power of counting , 1983 .

[15]  Jörg Rothe,et al.  Exact analysis of Dodgson elections: Lewis Carroll's 1876 voting system is complete for parallel access to NP , 1997, JACM.

[16]  Lane A. Hemachandra,et al.  The strong exponential hierarchy collapses , 1989 .

[17]  Arnold B. Urken,et al.  Classics of social choice , 1995 .

[18]  M. Trick,et al.  Voting schemes for which it can be difficult to tell who won the election , 1989 .

[19]  Klaus W. Wagner More Complicated Questions About Maxima and Minima, and Some Closures of NP , 1987, Theor. Comput. Sci..

[20]  Daniel G. Brown,et al.  A probabilistic analysis of a greedy algorithm arising from computational biology , 2001, SODA '01.

[21]  Leonid A. Levin,et al.  Average Case Complete Problems , 1986, SIAM J. Comput..

[22]  T. Tideman,et al.  Independence of clones as a criterion for voting rules , 1987 .

[23]  Piotr Faliszewski,et al.  How Hard Is Bribery in Elections? , 2006, J. Artif. Intell. Res..

[24]  Ronald L. Rivest,et al.  Introduction to Algorithms , 1990 .

[25]  Friedrich Pukelsheim,et al.  The electoral writings of Ramon Llull , 2001 .

[26]  Jörg Vogel,et al.  Theta2p-Completeness: A Classical Approach for New Results , 2000, FSTTCS.

[27]  Noga Alon,et al.  The Probabilistic Method , 2015, Fundamentals of Ramsey Theory.

[28]  Vincent Conitzer,et al.  Nonexistence of Voting Rules That Are Usually Hard to Manipulate , 2006, AAAI.

[29]  Michael R. Fellows,et al.  Parameterized Complexity , 1998 .

[30]  Clifford Stein,et al.  Introduction to Algorithms, 2nd edition. , 2001 .

[31]  Luca Trevisan,et al.  Lecture Notes on Computational Complexity , 2004 .

[32]  Matteo Marsili,et al.  Statistical mechanics model for the emergence of consensus. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[33]  Hendrik W. Lenstra,et al.  Integer Programming with a Fixed Number of Variables , 1983, Math. Oper. Res..

[34]  Piotr Faliszewski,et al.  Llull and Copeland Voting Broadly Resist Bribery and Control , 2007, AAAI.

[35]  D. Spielman,et al.  Smoothed analysis of algorithms: Why the simplex algorithm usually takes polynomial time , 2004 .

[36]  H. Chernoff A Measure of Asymptotic Efficiency for Tests of a Hypothesis Based on the sum of Observations , 1952 .

[37]  Rolf Niedermeier,et al.  Invitation to Fixed-Parameter Algorithms , 2006 .

[38]  Juris Hartmanis,et al.  The Boolean Hierarchy I: Structural Properties , 1988, SIAM J. Comput..

[39]  D. Black The theory of committees and elections , 1959 .

[40]  Ariel D. Procaccia,et al.  Junta Distributions and the Average-Case Complexity of Manipulating Elections , 2007, J. Artif. Intell. Res..

[41]  Lefteris M. Kirousis,et al.  The probabilistic analysis of a greedy satisfiability algorithm , 2002, Random Struct. Algorithms.

[42]  Luca Trevisan,et al.  On Worst-Case to Average-Case Reductions for NP Problems , 2005, Electron. Colloquium Comput. Complex..

[43]  Jie Wang,et al.  Average-Case Intractable NP Problems , 1997, Advances in Algorithms, Languages, and Complexity.

[44]  Noga Alon,et al.  The Probabilistic Method, Second Edition , 2004 .

[45]  Piotr Faliszewski,et al.  The Complexity of Bribery in Elections , 2006, AAAI.

[46]  P.-C.-F. Daunou,et al.  Mémoire sur les élections au scrutin , 1803 .

[47]  Jie Wang,et al.  Average-case computational complexity theory , 1998 .

[48]  Peter Slavík A Tight Analysis of the Greedy Algorithm for Set Cover , 1997, J. Algorithms.