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Game theory evolving: a problem-centered introduction to modeling strategic interaction

개인저자
Herbert Gintis
판사항
2nd ed
발행사항
Princeton : Princeton University Press, 2009
형태사항
xvii, 390 p.: ill. ; 26cm
ISBN
9780691140513
청구기호
300.1 G493g
서지주기
Includes bibliographical references (p. 375-383) and index
소장정보
위치등록번호청구기호 / 출력상태반납예정일
이용 가능 (1)
1자료실00013428대출가능-
이용 가능 (1)
  • 등록번호
    00013428
    상태/반납예정일
    대출가능
    -
    위치/청구기호(출력)
    1자료실
책 소개

Since its original publication in 2000, Game Theory Evolving has been considered the best textbook on evolutionary game theory. This completely revised and updated second edition of Game Theory Evolving contains new material and shows students how to apply game theory to model human behavior in ways that reflect the special nature of sociality and individuality. The textbook continues its in-depth look at cooperation in teams, agent-based simulations, experimental economics, the evolution and diffusion of preferences, and the connection between biology and economics.


Recognizing that students learn by doing, the textbook introduces principles through practice. Herbert Gintis exposes students to the techniques and applications of game theory through a wealth of sophisticated and surprisingly fun-to-solve problems involving human and animal behavior. The second edition includes solutions to the problems presented and information related to agent-based modeling. In addition, the textbook incorporates instruction in using mathematical software to solve complex problems. Game Theory Evolving is perfect for graduate and upper-level undergraduate economics students, and is a terrific introduction for ambitious do-it-yourselfers throughout the behavioral sciences.


  • Revised and updated edition relevant for courses across disciplines

  • Perfect for graduate and upper-level undergraduate economics courses

  • Solutions to problems presented throughout

  • Incorporates instruction in using computational software for complex problem solving

  • Includes in-depth discussions of agent-based modeling