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6
Chapter Three: Related Work
This work is motivated by the various algorithms developed to compute optimal defender strategies in Stackelberg games. These algorithms have been designed taking into consideration the different aspects of human decision making such as risk/loss aversion, non-linear weighing of probabilities and bounded rationality.
Prospect Theory
Prospect Theory (PT) describes a simple form of game involving alternatives that involve risk where the probabilities are known. The model tries to model real-life choices rather than optimal decisions. This theory describes the decision making process as maximization of the prospect which in general, has close proximity to what is referred to as expected utility by other models. The theory describes how individuals evaluate potential losses and gains. The decision-making is based on the editing of the choices to determine what humans equate as similar outcomes followed by the evaluation of the choices obtained through the calculation of utility value. The general principles of probability do not hold well as the payoff values and the assigned probabilities are perceived lower than what they actually signify. An empirical form of the function is shown in Figure 1.
Object Description
| Title | Computational model of human behavior in security games with varying number of targets |
| Author | Goenka, Mohit |
| Author email | mgoenka@usc.edu; mohitgoenka@gmail.com |
| Degree | Master of Science |
| Document type | Thesis |
| Degree program | Computer Science |
| School | Viterbi School of Engineering |
| Date defended/completed | 2011-03-30 |
| Date submitted | 2011 |
| Restricted until | Unrestricted |
| Date published | 2011-04-19 |
| Advisor (committee chair) | Tambe, Milind |
| Advisor (committee member) |
John, Richard S. Maheswaran, Rajiv T. |
| Abstract | Security is one of the biggest concerns all around the world. There are only a limited number of resources that can be allocated in security coverage. Terrorists can exploit any pattern of monitoring deployed by the security personnel. It becomes important to make the security pattern unpredictable and randomized. In such a scenario, the security forces can be randomized using algorithms based on Stackelberg games.; Stackelberg games have recently gained significant importance in deployment for real world security. Game-theoretic techniques make a standard assumption that adversaries' actions are perfectly rational. It is a challenging task to account for human behavior in such circumstances.; What becomes more challenging in applying game-theoretic techniques to real-world security problems is the standard assumption that the adversary is perfectly rational in responding to security forces' strategy, which can be unrealistic for human adversaries. Different models in the form of PT, PT-Attract, COBRA, DOBSS and QRE have already been proposed to address the scenario in settings with fixed number of targets. My work focuses on the evaluation of these models when the number of targets is varied, giving rise to an entirely new problem set. |
| Keyword | artificial intelligence; behavioral sciences; game theory; human behavior; COBRA; DOBSS; PT; PT-Attract; QRE; Stackelberg |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m3757 |
| Contributing entity | University of Southern California |
| Rights | Goenka, Mohit |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | cisadmin@lib.usc.edu |
| Filename | etd-Goenka-4204 |
| Archival file | uscthesesreloadpub_Volume62/etd-Goenka-4204.pdf |
Description
| Title | Page 21 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | 6 Chapter Three: Related Work This work is motivated by the various algorithms developed to compute optimal defender strategies in Stackelberg games. These algorithms have been designed taking into consideration the different aspects of human decision making such as risk/loss aversion, non-linear weighing of probabilities and bounded rationality. Prospect Theory Prospect Theory (PT) describes a simple form of game involving alternatives that involve risk where the probabilities are known. The model tries to model real-life choices rather than optimal decisions. This theory describes the decision making process as maximization of the prospect which in general, has close proximity to what is referred to as expected utility by other models. The theory describes how individuals evaluate potential losses and gains. The decision-making is based on the editing of the choices to determine what humans equate as similar outcomes followed by the evaluation of the choices obtained through the calculation of utility value. The general principles of probability do not hold well as the payoff values and the assigned probabilities are perceived lower than what they actually signify. An empirical form of the function is shown in Figure 1. |
