Social Choice Theory By Shiyan Li. History The theory of social choice and voting has had a long history in the social sciences, dating back to early.

Slides:



Advertisements
Similar presentations
A Simple Proof "There is no consistent method by which a democratic society can make a choice (when voting) that is always fair when that choice must be.
Advertisements

CS 886: Electronic Market Design Social Choice (Preference Aggregation) September 20.
Introduction to Game theory Presented by: George Fortetsanakis.
Math for Liberal Studies.  In most US elections, voters can only cast a single ballot for the candidate he or she likes the best  However, most voters.
Arrow’s impossibility theorem EC-CS reading group Kenneth Arrow Journal of Political Economy, 1950.
Basic Structures: Sets, Functions, Sequences, Sums, and Matrices
Basic Structures: Sets, Functions, Sequences, Sums, and Matrices
Week 21 Basic Set Theory A set is a collection of elements. Use capital letters, A, B, C to denotes sets and small letters a 1, a 2, … to denote the elements.
Social Choice: The Impossible Dream Michelle Blessing February 23, 2010 Michelle Blessing February 23, 2010.
1.  Detailed Study of groups is a fundamental concept in the study of abstract algebra. To define the notion of groups,we require the concept of binary.
Mechanism Design and the VCG mechanism The concept of a “mechanism”. A general (abstract) solution for welfare maximization: the VCG mechanism. –This is.
Motivation: Condorcet Cycles Let people 1, 2 and 3 have to make a decision between options A, B, and C. Suppose they decide that majority voting is a good.
1 By Gil Kalai Institute of Mathematics and Center for Rationality, Hebrew University, Jerusalem, Israel presented by: Yair Cymbalista.
Logic and Set Theory.
Induction Sections 41. and 4.2 of Rosen Fall 2008 CSCE 235 Introduction to Discrete Structures Course web-page: cse.unl.edu/~cse235 Questions:
Social choice theory = preference aggregation = voting assuming agents tell the truth about their preferences Tuomas Sandholm Professor Computer Science.
Discrete Structures Chapter 5 Relations and Functions Nurul Amelina Nasharuddin Multimedia Department.
INFINITE SEQUENCES AND SERIES
Social Choice Theory By Shiyan Li. History The theory of social choice and voting has had a long history in the social sciences, dating back to early.
1 Manipulation of Voting Schemes: A General Result By Allan Gibbard Presented by Rishi Kant.
Social choice theory = preference aggregation = truthful voting Tuomas Sandholm Professor Computer Science Department Carnegie Mellon University.
NOTE: To change the image on this slide, select the picture and delete it. Then click the Pictures icon in the placeholder to insert your own image. CHOOSING.
A Fourier-Theoretic Perspective on the Condorcet Paradox and Arrow ’ s Theorem. By Gil Kalai, Institute of Mathematics, Hebrew University Presented by:
Decision Theory CHOICE (Social Choice) Professor : Dr. Liang Student : Kenwa Chu.
Methods of Proof & Proof Strategies
Induction and recursion
Chapter 1 Probability and Distributions Math 6203 Fall 2009 Instructor: Ayona Chatterjee.
1 Discrete Structures – CNS2300 Text Discrete Mathematics and Its Applications (5 th Edition) Kenneth H. Rosen Chapter 4 Counting.
MATH 224 – Discrete Mathematics
Basic Concepts of Discrete Probability (Theory of Sets: Continuation) 1.
March 3, 2015Applied Discrete Mathematics Week 5: Mathematical Reasoning 1Arguments Just like a rule of inference, an argument consists of one or more.
Discrete Mathematics Math Review. Math Review: Exponents, logarithms, polynomials, limits, floors and ceilings* * This background review is useful for.
CSE 311 Foundations of Computing I Lecture 8 Proofs and Set Theory Spring
1 Sections 1.5 & 3.1 Methods of Proof / Proof Strategy.
Elections and Strategic Voting: Condorcet and Borda E. Maskin Harvard University.
1 Elections and Manipulations: Ehud Friedgut, Gil Kalai, and Noam Nisan Hebrew University of Jerusalem and EF: U. of Toronto, GK: Yale University, NN:
Week 11 What is Probability? Quantification of uncertainty. Mathematical model for things that occur randomly. Random – not haphazard, don’t know what.
April 14, 2015Applied Discrete Mathematics Week 10: Equivalence Relations 1 Properties of Relations Definition: A relation R on a set A is called transitive.
Copyright © Curt Hill Quantifiers. Copyright © Curt Hill Introduction What we have seen is called propositional logic It includes.
CS201: Data Structures and Discrete Mathematics I
Chapter 10: The Manipulability of Voting Systems Lesson Plan An Introduction to Manipulability Majority Rule and Condorcet’s Method The Manipulability.
1 EC9A4 Social Choice and Voting Lecture 2 EC9A4 Social Choice and Voting Lecture 2 Prof. Francesco Squintani
A Logic of Partially Satisfied Constraints Nic Wilson Cork Constraint Computation Centre Computer Science, UCC.
Math for Liberal Studies.  We have seen many methods, all of them flawed in some way  Which method should we use?  Maybe we shouldn’t use any of them,
CSE 311 Foundations of Computing I Lecture 9 Proofs and Set Theory Autumn 2012 CSE
Chapter 3 Preferences.
Conditional Probability Mass Function. Introduction P[A|B] is the probability of an event A, giving that we know that some other event B has occurred.
Theorem The square of any odd integer has the form 8m + 1 for some integer m.
CS 103 Discrete Structures Lecture 13 Induction and Recursion (1)
Theorem: Equal weight implies equal power but not the converse.
6.853: Topics in Algorithmic Game Theory Fall 2011 Constantinos Daskalakis Lecture 22.
Social choice theory = preference aggregation = voting assuming agents tell the truth about their preferences Tuomas Sandholm Professor Computer Science.
Discrete Mathematics CS 2610 February 10, Agenda Previously Functions And now Finish functions Start Boolean algebras (Sec. 11.1)
Decisions How do we make choices?. Types of Decisions Individual—our opinion is our decision. Group—Individual opinions are expressed by voting(at least.
Basic probability Sep. 16, Introduction Our formal study of probability will base on Set theory Axiomatic approach (base for all our further studies.
Network Systems Lab. Korea Advanced Institute of Science and Technology No.1 Ch. 3 Iterative Method for Nonlinear problems EE692 Parallel and Distribution.
CSE 311: Foundations of Computing Fall 2013 Lecture 8: Proofs and Set theory.
How Should Presidents Be Elected? E. Maskin Institute for Advanced Study.
The mathematics of voting The paradoxes of democracy.
Chapter 9: Social Choice: The Impossible Dream Lesson Plan Voting and Social Choice Majority Rule and Condorcet’s Method Other Voting Systems for Three.
Foundations of Discrete Mathematics Chapter 1 By Dr. Dalia M. Gil, Ph.D.
Basic Probability. Introduction Our formal study of probability will base on Set theory Axiomatic approach (base for all our further studies of probability)
Arrow’s Impossibility Theorem
3.3 Mathematical Induction 1 Follow me for a walk through...
Functions of Complex Variable and Integral Transforms
Chapter 10: The Manipulability of Voting Systems Lesson Plan
Social choice theory = preference aggregation = voting assuming agents tell the truth about their preferences Tuomas Sandholm Professor Computer Science.
Applied Discrete Mathematics Week 2: Proofs
Voting systems Chi-Kwong Li.
Computer Security: Art and Science, 2nd Edition
Presentation transcript:

Social Choice Theory By Shiyan Li

History The theory of social choice and voting has had a long history in the social sciences, dating back to early work of Marquis de Condorcet (the 1st rigorous mathematical treatment of voting) and others in the 18th century. The theory of social choice and voting has had a long history in the social sciences, dating back to early work of Marquis de Condorcet (the 1st rigorous mathematical treatment of voting) and others in the 18th century. Now it is a branch of discrete mathematics. Now it is a branch of discrete mathematics.

Purpose Social Choice Theory is the study of systems and institution for making collective choice, choices that affect a group of people. Social Choice Theory is the study of systems and institution for making collective choice, choices that affect a group of people. Be used in multi-agent planning, collective decision, computerized election and so on. Be used in multi-agent planning, collective decision, computerized election and so on. Voters Alternatives

Simple Majority Voting Choose one from two possible alternatives by a group of participants. Choose one from two possible alternatives by a group of participants. Consider a democratic voting situation. Consider a democratic voting situation.

Preferences and Outcome Alternatives: x or y Alternatives: x or y Every voter has a preferences. Every voter has a preferences. Three possible situations of each voter ’ s preference: i) x is strictly better than y: +1 ii) y is strictly better than x: -1 iii) x and y are equivalent: 0 Three possible situations of each voter ’ s preference: i) x is strictly better than y: +1 ii) y is strictly better than x: -1 iii) x and y are equivalent: 0 After the voting: i) x is winner: +1 ii) y is winner: -1 iii) x and y tie: 0 After the voting: i) x is winner: +1 ii) y is winner: -1 iii) x and y tie: 0

General List Use a list to describe a collection of n voters ’ preferences e.g. (-1, +1, 0, 0, -1, …, +1, -1) Use a list to describe a collection of n voters ’ preferences e.g. (-1, +1, 0, 0, -1, …, +1, -1) General List: D = (d 1, d 2, d 3, …, d n-1, d n ) d i is +1, -1 or 0 depending on whether individual i strictly prefers x to y, y to x or is indifferent between them. General List: D = (d 1, d 2, d 3, …, d n-1, d n ) d i is +1, -1 or 0 depending on whether individual i strictly prefers x to y, y to x or is indifferent between them. n entries

General List Consider the sum of list D: When d 1 +d 2 +d 3 + … +d n-1 +d n > 0, x is to be chosen, simple majority voting assigns +1. When d 1 +d 2 +d 3 + … +d n-1 +d n 0, x and y tie, simple majority voting assigns 0. Consider the sum of list D: When d 1 +d 2 +d 3 + … +d n-1 +d n > 0, x is to be chosen, simple majority voting assigns +1. When d 1 +d 2 +d 3 + … +d n-1 +d n 0, x and y tie, simple majority voting assigns 0.

Formal Definition of Simple Majority Vote Use the sign function to formally define the simple majority vote: (d 1, d 2, …, d n ) sgn(d 1 +d 2 + … +d n ) Use the sign function to formally define the simple majority vote: (d 1, d 2, …, d n ) sgn(d 1 +d 2 + … +d n ) Function N +1 and N -1 : N +1 : associates with a list D the number of d i ‘ s that are strictly positive N -1 : associates with a list D the number of d i ‘ s that are strictly positive Function N +1 and N -1 : N +1 : associates with a list D the number of d i ‘ s that are strictly positive N -1 : associates with a list D the number of d i ‘ s that are strictly positive

Formal Definition of Simple Majority Vote E.g.: for list D = (+1, -1, -1,0, +1, +1), ∵ n = 6, n/2 = 3, N +1 (+1, -1, -1,0, +1, +1) = 3 > n/2 N -1 (+1, -1, -1,0, +1, +1) = 2 n/2 N -1 (+1, -1, -1,0, +1, +1) = 2 <n/2 ∴ g(+1, -1, -1,0, +1, +1) = +1 g (d 1, d 2, d 3, …, d n ) = +1 if N +1 (d 1, d 2, d 3, …, d n ) > n/2 -1 if N -1 (d 1, d 2, d 3, …, d n ) > n/2 0 otherwise

Rule of Simple Majority Voting Social Choice Rule: is a function f(d 1, d 2, …, d n ), the domain of the function is the set of all list to which f assigns some unambiguous outcome: +1, -1 or 0. Social Choice Rule: is a function f(d 1, d 2, …, d n ), the domain of the function is the set of all list to which f assigns some unambiguous outcome: +1, -1 or 0. A social choice rule of simple majority voting can be characterized by 4 properties (Kenneth O. May, 1952). A social choice rule of simple majority voting can be characterized by 4 properties (Kenneth O. May, 1952).

Property 1 of Rule f Property 1 – Universal Domain: f satisfies universal domain if it has a domain equal to all logically possible lists (i.e. any combination of the individual voters ’ preferences) of n entries of +1, -1 or 0. Property 1 – Universal Domain: f satisfies universal domain if it has a domain equal to all logically possible lists (i.e. any combination of the individual voters ’ preferences) of n entries of +1, -1 or 0.

Property 2 of Rule f One-to-one Correspondence: is a function s from the set {1, 2, …, n} to itself such that s is defined on every integer from 1 to n and no outcome is assigned to two different integers: s(i) = s(j) implies i = j. One-to-one Correspondence: is a function s from the set {1, 2, …, n} to itself such that s is defined on every integer from 1 to n and no outcome is assigned to two different integers: s(i) = s(j) implies i = j. one-to-one correspondence S(i)i not one-to-one correspondence S(i)i i i

Property 2 of Rule f Permutation: Given two lists D = (d 1, d 2, …, d n ) and D ’ = (d 1 ’, d 2 ’, …, d n ’ ) say that D and D ’ are permutation of one another if there is a one-to-one correspondence s on {1, 2, …, n} such that d s(i) ’ = d i. Permutation: Given two lists D = (d 1, d 2, …, d n ) and D ’ = (d 1 ’, d 2 ’, …, d n ’ ) say that D and D ’ are permutation of one another if there is a one-to-one correspondence s on {1, 2, …, n} such that d s(i) ’ = d i. E.g.: voter: (+1, +1, +1, 0, 0, -1, -1) and voter: (-1, 0, +1, +1, 0, -1, +1) are permutation of one another via the one-to-one correspondence: 1->3, 2->4, 3->7, 4->2, 5->5, 6->1, 7->6. E.g.: voter: (+1, +1, +1, 0, 0, -1, -1) and voter: (-1, 0, +1, +1, 0, -1, +1) are permutation of one another via the one-to-one correspondence: 1->3, 2->4, 3->7, 4->2, 5->5, 6->1, 7->6.

Property 2 of Rule f Property 2 – Anonymity: A social choice rule will satisfy this property if it does not make any difference who votes in which way as long as the numbers of each type are the same (i.e. equal treatment of each voter). Formal Definition: A social choice rule f satisfies anonymity if whenever (d 1, d 2, …, d n ) and (d 1 ’, d 2 ’, …, d n ’) in the domain of f are permutations of one another then f(d 1, d 2, …, d n ) = f(d 1 ’, d 2 ’, …, d n ’) E.g.: if D = (+1, +1, +1, 0, 0, -1, -1) and D ’ = (-1, 0, +1, +1, 0, -1, +1) so D and D ’ are permutations of each other, and if f(d 1, d 2, …, d n ) = f(d 1 ’, d 2 ’, …, d n ’) then social choice rule f satisfies anonymity. Property 2 – Anonymity: A social choice rule will satisfy this property if it does not make any difference who votes in which way as long as the numbers of each type are the same (i.e. equal treatment of each voter). Formal Definition: A social choice rule f satisfies anonymity if whenever (d 1, d 2, …, d n ) and (d 1 ’, d 2 ’, …, d n ’) in the domain of f are permutations of one another then f(d 1, d 2, …, d n ) = f(d 1 ’, d 2 ’, …, d n ’) E.g.: if D = (+1, +1, +1, 0, 0, -1, -1) and D ’ = (-1, 0, +1, +1, 0, -1, +1) so D and D ’ are permutations of each other, and if f(d 1, d 2, …, d n ) = f(d 1 ’, d 2 ’, …, d n ’) then social choice rule f satisfies anonymity.

Property 3 of Rule f Property 3 – Neutrality: A social choice rule satisifies neutrality if whenever (d 1, d 2, …, d n ) and (-d 1, -d 2, …, -d n ) are both the domain of f then f(d 1, d 2, …, d n )=-f(-d 1, -d 2, …, -d n ) Property 3 – Neutrality: A social choice rule satisifies neutrality if whenever (d 1, d 2, …, d n ) and (-d 1, -d 2, …, -d n ) are both the domain of f then f(d 1, d 2, …, d n )=-f(-d 1, -d 2, …, -d n ) Note: The condition of anonymity is a way of treating individuals equally, the condition of neutrality is a way of treating alternatives x and y equally. Note: The condition of anonymity is a way of treating individuals equally, the condition of neutrality is a way of treating alternatives x and y equally.

Property 4 of Rule f i-Variants: Suppose there are D = (d 1, d 2, …, d n ) and D ’ = (d 1 ’, d 2 ’, …, d n ’ ); D and D ’ are i-variants if for all j≠i, d j =d j ’. Thus two i-variants differ in at most the ith entry. (Note: It has not strictly stipulated the relationship of d i and d i ’, i.e., it is possible that d i =d i ’, d i >d i ’, or d i d i ’, or d i <d i ’.) E.g.: Two lists D = (+1, -1, -1, 0, +1, -1, +1) and D ’ = (+1, -1, 0, 0, +1, -1, +1) are 3-variants since they differ only at the third place E.g.: Two lists D = (+1, -1, -1, 0, +1, -1, +1) and D ’ = (+1, -1, 0, 0, +1, -1, +1) are 3-variants since they differ only at the third place

Property 4 of Rule f Purpose: Simple majority voting can not be strictly characterized by property 1~3 yet (unresponsive). Purpose: Simple majority voting can not be strictly characterized by property 1~3 yet (unresponsive). E.g.: Assume a constant rule (function) const 0 (D) that always generates result 0 for any point in its domain. i.e. const 0 (D) 0 This constant rule satisfies all 3 properties mentioned above. D contains all logically possible lists. – Property 1 For all permutations D ’, const 0 (D) = const 0 (D) = 0. – Property 2 For all lists in D, const 0 (D) = -const 0 (-D) = 0. – Property 3 So, we still need a property to constrain rule f to simple majority more strictly. E.g.: Assume a constant rule (function) const 0 (D) that always generates result 0 for any point in its domain. i.e. const 0 (D) 0 This constant rule satisfies all 3 properties mentioned above. D contains all logically possible lists. – Property 1 For all permutations D ’, const 0 (D) = const 0 (D) = 0. – Property 2 For all lists in D, const 0 (D) = -const 0 (-D) = 0. – Property 3 So, we still need a property to constrain rule f to simple majority more strictly.

Property 4 of Rule f Property 4 – Positive Responsiveness: f satisfies positive responsiveness if for all i, whenever (d 1, d 2, …, d n ) and (d 1 ’, d 2 ’, …, d n ’ ) are i-variants with di ’ > di, then f(d 1, d 2, …, d n ) ≥ 0 implies f(d 1 ’, d 2 ’, …, d n ’ ) = +1. Property 4 – Positive Responsiveness: f satisfies positive responsiveness if for all i, whenever (d 1, d 2, …, d n ) and (d 1 ’, d 2 ’, …, d n ’ ) are i-variants with di ’ > di, then f(d 1, d 2, …, d n ) ≥ 0 implies f(d 1 ’, d 2 ’, …, d n ’ ) = +1.

Property 4 of Rule f Positive responsiveness can be inferred by multi i-variants. E.g.: Suppose to apply lists #1 below to f which is a rule satisfies positive responsiveness: f(+1, 0, -1, 0, 0, +1, -1) = 0. First find a 3-variant list #2 of #1: (+1, 0, 0, 0, 0, +1, -1), so f(+1, 0, 0, 0, 0, +1, -1) = +1. Second find a 4-variant list #3 of #2: (+1, 0, 0, +1, 0, +1, -1), so f(+1, 0, 0, +1, 0, +1, -1) = +1. Then it can be concluded that f(+1, 0, -1, 0, 0, +1, -1) = 0 implies f(+1, 0, 0, +1, 0, +1, -1) = +1, although list #1 and #3 are not i-variants. Positive responsiveness can be inferred by multi i-variants. E.g.: Suppose to apply lists #1 below to f which is a rule satisfies positive responsiveness: f(+1, 0, -1, 0, 0, +1, -1) = 0. First find a 3-variant list #2 of #1: (+1, 0, 0, 0, 0, +1, -1), so f(+1, 0, 0, 0, 0, +1, -1) = +1. Second find a 4-variant list #3 of #2: (+1, 0, 0, +1, 0, +1, -1), so f(+1, 0, 0, +1, 0, +1, -1) = +1. Then it can be concluded that f(+1, 0, -1, 0, 0, +1, -1) = 0 implies f(+1, 0, 0, +1, 0, +1, -1) = +1, although list #1 and #3 are not i-variants.

Property 4 of Rule f “ Negative Responsiveness ” : Suppose rule f satisfies property 1~4. For all i, whenever D = (d 1, d 2, …, d n ) and D ’ = (d 1 ‘, d 2 ‘, …, d n ‘ ) are i- variants with d i ‘ -d i ). If f(D) ≤ 0 then f(-D) = -f(D) ≥ 0 by neutrality. So f(-D) ≥ 0. There is a list -D’ which together with –D are i-variants with -d i ‘ > -d i. Because f(-D) ≥ 0 so that f(-D’) = +1 by positive responsiveness. So f(D’) = -f(-D’) = -1 For summary: If f satisfies positive responsiveness and neutrality then for all i, whenever D = (d 1, d 2, …, d n ) and D ’ = (d 1 ‘, d 2 ‘, …, d n ‘ ) are i-variants with d i ‘ -d i ). If f(D) ≤ 0 then f(-D) = -f(D) ≥ 0 by neutrality. So f(-D) ≥ 0. There is a list -D’ which together with –D are i-variants with -d i ‘ > -d i. Because f(-D) ≥ 0 so that f(-D’) = +1 by positive responsiveness. So f(D’) = -f(-D’) = -1 For summary: If f satisfies positive responsiveness and neutrality then for all i, whenever D = (d 1, d 2, …, d n ) and D ’ = (d 1 ‘, d 2 ‘, …, d n ‘ ) are i-variants with d i ‘ < d i, such that f(D) ≤ 0 implies f(D’) = -1

May’s Theorem Simple majority voting is the only rule that satisfies all four properties (or conditions) simultaneously. Simple majority voting is the only rule that satisfies all four properties (or conditions) simultaneously.

May’s Theorem May ’ s Theorem: If a social choice rule f satisfies all of i) universal domain ii) anonymity iii) neutrality iv) positive responsiveness then f is simple majority voting. May ’ s Theorem: If a social choice rule f satisfies all of i) universal domain ii) anonymity iii) neutrality iv) positive responsiveness then f is simple majority voting.

Proof of May’s Theory Step 1: If rule f satisfies conditions i), ii), iii) and iv). So the value of f(D) only depends on the number of +1 ’ s, 0 ’ s and -1 ’ s by anonymity. Suppose there are n elements in D, N +1 (D) and N -1 (D) is the number of +1 ’ s and -1 ’ s in D correspondingly. So the number of 0 ’ s is n - N +1 (D) - N -1 (D). Therefore, f(D) is entirely determined by N +1 (D) and N -1 (D) by anonymity. Step 1: If rule f satisfies conditions i), ii), iii) and iv). So the value of f(D) only depends on the number of +1 ’ s, 0 ’ s and -1 ’ s by anonymity. Suppose there are n elements in D, N +1 (D) and N -1 (D) is the number of +1 ’ s and -1 ’ s in D correspondingly. So the number of 0 ’ s is n - N +1 (D) - N -1 (D). Therefore, f(D) is entirely determined by N +1 (D) and N -1 (D) by anonymity.

Proof of May’s Theory Step 2: Suppose N +1 (D) = N -1 (D) and f(D) = r. Obviously N +1 (D) = N -1 (D) = N +1 (-D) #1 N -1 (D) = N +1 (D) = N -1 (-D). #2 And because f satisfies universal domain, so f is also defined at – D. Since f(-D) = -f(D) = -r by neutrality, and f(-D) = f(D) = r by #1 and #2. Combining above results, – r = r so r = 0. That is N +1 (D) = N -1 (D) implies f(D) = 0. Step 2: Suppose N +1 (D) = N -1 (D) and f(D) = r. Obviously N +1 (D) = N -1 (D) = N +1 (-D) #1 N -1 (D) = N +1 (D) = N -1 (-D). #2 And because f satisfies universal domain, so f is also defined at – D. Since f(-D) = -f(D) = -r by neutrality, and f(-D) = f(D) = r by #1 and #2. Combining above results, – r = r so r = 0. That is N +1 (D) = N -1 (D) implies f(D) = 0.

Proof of May’s Theory Step 3: Suppose N +1 (D) > N -1 (D) where there are n elements in D, so that N +1 (D) = N -1 (D) + m where 0 N -1 (D), then f(D) = +1 If N +1 (D) N -1 (D) where there are n elements in D, so that N +1 (D) = N -1 (D) + m where 0 N -1 (D), then f(D) = +1 If N +1 (D) < N -1 (D), then f(D) = -1

Proof of May’s Theory Summary of Proof: From step 1, 2, and 3: If N +1 (D)=N -1 (D), then f(D)=0. If N +1 (D)>N -1 (D), then f(D)=+1. If N +1 (D) N -1 (D), then f(D)=+1. If N +1 (D)<N -1 (D), then f(D)=-1. These results just satisfy the formal definition of simple majority voting. So May ’ s theory is proved.

Voting Paradox To be continued … To be continued …

References Kelly, Jerry S., 1988, Social Choice Theory An Introduction, Springer- Verlag, Berlin Heidelberg. Kelly, Jerry S., 1988, Social Choice Theory An Introduction, Springer- Verlag, Berlin Heidelberg.