Modeling human adversary decision making in security games: An initial report

Thanh H. Nguyen; James Pita; Rajiv Maheswaran; Milind Tambe; Amos Azaria; Sarit Kraus

Modeling human adversary decision making in security games: An initial report

Thanh H. Nguyen, James Pita, Rajiv Maheswaran, Milind Tambe, Amos Azaria, Sarit Kraus

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

Abstract

Motivated by recent deployments of Stackelberg security games (SSGs), two competing approaches have emerged which either integrate models of human decision making into game-theoretic algorithms or apply robust optimization techniques that avoid adversary modeling. Recently, a robust technique (MATCH) has been shown to significantly outperform the leading modeling-based algorithms (e.g., Quantal Response (QR)) even in the presence of significant amounts of subject data. As a result, the effectiveness of using human behaviors in solving SSGs remains in question. We study this question in this paper.

Original language	English
Pages	1297-1298
Number of pages	2
State	Published - 2013
Externally published	Yes
Event	12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013 - Saint Paul, MN, United States Duration: 6 May 2013 → 10 May 2013

Conference

Conference	12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013
Country/Territory	United States
City	Saint Paul, MN
Period	6/05/13 → 10/05/13

Keywords

Bounded Rationality
Game Theory
Human Behavior
Quantal Response
Robust Optimization

Cite this

@conference{a5b422be8d564cd0b6c8a3bc55aeee06,

title = "Modeling human adversary decision making in security games: An initial report",

abstract = "Motivated by recent deployments of Stackelberg security games (SSGs), two competing approaches have emerged which either integrate models of human decision making into game-theoretic algorithms or apply robust optimization techniques that avoid adversary modeling. Recently, a robust technique (MATCH) has been shown to significantly outperform the leading modeling-based algorithms (e.g., Quantal Response (QR)) even in the presence of significant amounts of subject data. As a result, the effectiveness of using human behaviors in solving SSGs remains in question. We study this question in this paper.",

keywords = "Bounded Rationality, Game Theory, Human Behavior, Quantal Response, Robust Optimization",

author = "Nguyen, {Thanh H.} and James Pita and Rajiv Maheswaran and Milind Tambe and Amos Azaria and Sarit Kraus",

year = "2013",

language = "אנגלית",

pages = "1297--1298",

note = "12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013 ; Conference date: 06-05-2013 Through 10-05-2013",

}

TY - CONF

T1 - Modeling human adversary decision making in security games

T2 - 12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013

AU - Nguyen, Thanh H.

AU - Pita, James

AU - Maheswaran, Rajiv

AU - Tambe, Milind

AU - Azaria, Amos

AU - Kraus, Sarit

PY - 2013

Y1 - 2013

N2 - Motivated by recent deployments of Stackelberg security games (SSGs), two competing approaches have emerged which either integrate models of human decision making into game-theoretic algorithms or apply robust optimization techniques that avoid adversary modeling. Recently, a robust technique (MATCH) has been shown to significantly outperform the leading modeling-based algorithms (e.g., Quantal Response (QR)) even in the presence of significant amounts of subject data. As a result, the effectiveness of using human behaviors in solving SSGs remains in question. We study this question in this paper.

AB - Motivated by recent deployments of Stackelberg security games (SSGs), two competing approaches have emerged which either integrate models of human decision making into game-theoretic algorithms or apply robust optimization techniques that avoid adversary modeling. Recently, a robust technique (MATCH) has been shown to significantly outperform the leading modeling-based algorithms (e.g., Quantal Response (QR)) even in the presence of significant amounts of subject data. As a result, the effectiveness of using human behaviors in solving SSGs remains in question. We study this question in this paper.

KW - Bounded Rationality

KW - Game Theory

KW - Human Behavior

KW - Quantal Response

KW - Robust Optimization

UR - http://www.scopus.com/inward/record.url?scp=84899444139&partnerID=8YFLogxK

M3 - ???researchoutput.researchoutputtypes.contributiontoconference.paper???

AN - SCOPUS:84899444139

SP - 1297

EP - 1298

Y2 - 6 May 2013 through 10 May 2013

ER -

Modeling human adversary decision making in security games: An initial report

Abstract

Conference

Keywords

Other files and links

Fingerprint

Cite this