The Shapley Value in Knapsack Budgeted Games

  • Smriti Bhagat
  • Anthony Kim
  • S. Muthukrishnan
  • Udi Weinsberg
Conference paper

DOI: 10.1007/978-3-319-13129-0_8

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8877)
Cite this paper as:
Bhagat S., Kim A., Muthukrishnan S., Weinsberg U. (2014) The Shapley Value in Knapsack Budgeted Games. In: Liu TY., Qi Q., Ye Y. (eds) Web and Internet Economics. WINE 2014. Lecture Notes in Computer Science, vol 8877. Springer, Cham

Abstract

We propose the study of computing the Shapley value for a new class of cooperative games that we call budgeted games, and investigate in particular knapsack budgeted games, a version modeled after the classical knapsack problem. In these games, the “value” of a set S of agents is determined only by a critical subset T ⊆ S of the agents and not the entirety of S due to a budget constraint that limits how large T can be. We show that the Shapley value can be computed in time faster than by the naïve exponential time algorithm when there are sufficiently many agents, and also provide an algorithm that approximates the Shapley value within an additive error. For a related budgeted game associated with a greedy heuristic, we show that the Shapley value can be computed in pseudo-polynomial time. Furthermore, we generalize our proof techniques and propose what we term algorithmic representation framework that captures a broad class of cooperative games with the property of efficient computation of the Shapley value. The main idea is that the problem of determining the efficient computation can be reduced to that of finding an alternative representation of the games and an associated algorithm for computing the underlying value function with small time and space complexities in the representation size.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Smriti Bhagat
    • 1
  • Anthony Kim
    • 2
  • S. Muthukrishnan
    • 3
  • Udi Weinsberg
    • 1
  1. 1.Technicolor ResearchLos AltosUSA
  2. 2.Department of Computer ScienceStanford UniversityStanfordUSA
  3. 3.Department of Computer ScienceRutgers UniversityPiscatawayUSA

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