Using simulated annealing to calculate the trembles of trembling hand perfection

S. McDonald; L. Wagner

doi:10.1109/CEC.2003.1299400

Using simulated annealing to calculate the trembles of trembling hand perfection

S. McDonald, L. Wagner

Research output: Contribution to conference › Paper › peer-review

2 Citations (Scopus)

Abstract

Within the literature on noncooperative game theory, there have been a number of algorithms which will compute Nash equilibria. We show that the family of algorithms known as Markov chain Monte Carlo (MCMC) can be used to calculate Nash equilibria. MCMC is a type of Monte Carlo simulation that relies on Markov chains to ensure its regularity conditions. MCMC has been widely used throughout the statistics and optimization literature, where variants of this algorithm are known as simulated annealing. We show that there is interesting connection between the trembles that underlie the functioning of this algorithm and the type of Nash refinement known as trembling hand perfection. We show that it is possible to use simulated annealing to compute this refinement.

Original language	English
Pages	2482-2489
Number of pages	8
DOIs	https://doi.org/10.1109/CEC.2003.1299400
Publication status	Published - 2003
Externally published	Yes
Event	2003 Congress on Evolutionary Computation, CEC 2003 - Canberra, ACT, Australia Duration: 8 Dec 2003 → 12 Dec 2003

Conference

Conference	2003 Congress on Evolutionary Computation, CEC 2003
Country/Territory	Australia
City	Canberra, ACT
Period	8/12/03 → 12/12/03

ASJC Scopus subject areas

Computational Mathematics

Access to Document

10.1109/CEC.2003.1299400

Cite this

@conference{56323018e839484eaad6d40a484058d8,

title = "Using simulated annealing to calculate the trembles of trembling hand perfection",

abstract = "Within the literature on noncooperative game theory, there have been a number of algorithms which will compute Nash equilibria. We show that the family of algorithms known as Markov chain Monte Carlo (MCMC) can be used to calculate Nash equilibria. MCMC is a type of Monte Carlo simulation that relies on Markov chains to ensure its regularity conditions. MCMC has been widely used throughout the statistics and optimization literature, where variants of this algorithm are known as simulated annealing. We show that there is interesting connection between the trembles that underlie the functioning of this algorithm and the type of Nash refinement known as trembling hand perfection. We show that it is possible to use simulated annealing to compute this refinement.",

author = "S. McDonald and L. Wagner",

year = "2003",

doi = "10.1109/CEC.2003.1299400",

language = "English",

pages = "2482--2489",

note = "2003 Congress on Evolutionary Computation, CEC 2003 ; Conference date: 08-12-2003 Through 12-12-2003",

}

TY - CONF

T1 - Using simulated annealing to calculate the trembles of trembling hand perfection

AU - McDonald, S.

AU - Wagner, L.

PY - 2003

Y1 - 2003

N2 - Within the literature on noncooperative game theory, there have been a number of algorithms which will compute Nash equilibria. We show that the family of algorithms known as Markov chain Monte Carlo (MCMC) can be used to calculate Nash equilibria. MCMC is a type of Monte Carlo simulation that relies on Markov chains to ensure its regularity conditions. MCMC has been widely used throughout the statistics and optimization literature, where variants of this algorithm are known as simulated annealing. We show that there is interesting connection between the trembles that underlie the functioning of this algorithm and the type of Nash refinement known as trembling hand perfection. We show that it is possible to use simulated annealing to compute this refinement.

AB - Within the literature on noncooperative game theory, there have been a number of algorithms which will compute Nash equilibria. We show that the family of algorithms known as Markov chain Monte Carlo (MCMC) can be used to calculate Nash equilibria. MCMC is a type of Monte Carlo simulation that relies on Markov chains to ensure its regularity conditions. MCMC has been widely used throughout the statistics and optimization literature, where variants of this algorithm are known as simulated annealing. We show that there is interesting connection between the trembles that underlie the functioning of this algorithm and the type of Nash refinement known as trembling hand perfection. We show that it is possible to use simulated annealing to compute this refinement.

UR - http://www.scopus.com/inward/record.url?scp=67650700165&partnerID=8YFLogxK

U2 - 10.1109/CEC.2003.1299400

DO - 10.1109/CEC.2003.1299400

M3 - Paper

AN - SCOPUS:67650700165

SP - 2482

EP - 2489

T2 - 2003 Congress on Evolutionary Computation, CEC 2003

Y2 - 8 December 2003 through 12 December 2003

ER -

Using simulated annealing to calculate the trembles of trembling hand perfection

Abstract

Conference

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this