NONZERO-SUM STOCHASTIC GAMES

Abstract

The paper extends the basic work that has been done on zero-sum stochastic games to those that are nonzero-sum. Appropriately defined equilibrium points are shown to exist for both the case where the players seek to maximize the total value of their discounted period rewards and the case where they wish to maximize their average reward per period. For the latter case, conditions required on the structure of the Markov chains are less stringent than those imposed in previous work on zero-sum stochastic games, extensions to n-person games and underlying semi-Markov processes are discussed, and finding an equilibrium point is shown to be equivalent to solving a certain nonlinear programming problem.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1969
Accession Number
AD0692394

Entities

People

  • Philip D. Rogers

Organizations

  • University of California, Berkeley

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • California
  • Computer Programming
  • Dynamic Programming
  • Game Theory
  • Linear Programming
  • Markov Chains
  • Markov Processes
  • Nonlinear Programming
  • Operations Research
  • Point Theorem
  • Probability
  • Probability Distributions
  • Theorems
  • United States
  • Universities
  • Zero-Sum Games

Readers

  • Game Theory.
  • Statistical inference.