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
위치 | 등록번호 | 청구기호 / 출력 | 상태 | 반납예정일 |
---|---|---|---|---|
이용 가능 (1) | ||||
1자료실 | 00013428 | 대출가능 | - |
- 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