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A Theory of Optimal Agenda Design

McKelvey, Richard D. (1980) A Theory of Optimal Agenda Design. Social Science Working Paper, 264. California Institute of Technology , Pasadena, CA. (Unpublished)

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This paper formalizes the problem of designing optimal agendas for voting over finite alternative spaces, when voters are assumed to be "naive," (i.e., they do not vote strategically). The class of agendas considered here is quite broad, and includes, as special cases, such methods as pairwise voting, sequential and elimination procedures, partitioning schemes, and all binary procedures. Given individual preferences over the basic alternative space, and various assumptions about how individuals choose between subsets of alternatives, one can then formalize the problem of designing agendas as a dynamic programming problem and solve for optimal agendas, i.e., agendas having either the highest probability of leading to a given alternative or having the highest expected utility to the agenda setter. Illustrations are given showing how the methods can be applied in specific examples.

Item Type:Report or Paper (Working Paper)
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Additional Information:Revised. Originally dated to May 1979. Support for this research was provided by the National Science Foundation, Grant #SOC77-08291. I acknowledge the assistance of George Duncan for some discussions on probabilistic versions of the model, and Carl Lydick for help on the computer work. Published as McKelvey, Richard D. "A theory of optimal agenda design." Management Science 27.3 (1981): 303-321.
Group:Social Science Working Papers
Funding AgencyGrant Number
Subject Keywords:Voting, Information economics, Game theory, Dynamic programming, Parliamentary procedure, Logical givens, Expected utility, Social order, Meetings, Voting behavior
Series Name:Social Science Working Paper
Issue or Number:264
Record Number:CaltechAUTHORS:20171017-142454970
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:82429
Deposited By: Jacquelyn Bussone
Deposited On:17 Oct 2017 23:52
Last Modified:03 Oct 2019 18:54

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