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List of Tables Table 1: Sample Stackelberg game 4 Table 2: Count of randomly generated payoff structures 11 Table 3: Money paid to the participants 16 Table 4: Average Expected Utilities of Game Models for Cluster 1 18 Table 5: Average Expected Utilities of Game Models for Cluster 2 19 Table 6: Average Expected Utilities of Game Models for Cluster 3 20 Table 7: Average Expected Utilities of Game Models for Cluster 4 21 Table 8: Average Expected Utilities of Game Models for 3 Gates 22 Table 9: Average Expected Utilities of Game Models for 6 Gates 23 Table 10: Average Expected Utilities of Game Models for 9 Gates 24 Table 11: Average Expected Utilities of Game Models for 12 Gates 25 Table 12: Average Expected Utilities of Game Models for 15 Gates 26 Table 13: Average Expected Utilities for PT Model 27 Table 14: Average Expected Utilities for PT-Attract Model 28 Table 15: Average Expected Utilities for COBRA (α = 0.15) Model 29 Table 16: Average Expected Utilities for COBRA (α = 0.5) Model 30 Table 17: Average Expected Utilities for DOBSS Model 31 Table 18: Average Expected Utilities for QRE (λ = 0.45) Model 32 Table 19: Average Expected Utilities for QRE (λ = 0.76) Model 33 Table 20: Time Weighted Average Expected Utilities against No. of Gates for Cluster 1 35
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 5 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | v List of Tables Table 1: Sample Stackelberg game 4 Table 2: Count of randomly generated payoff structures 11 Table 3: Money paid to the participants 16 Table 4: Average Expected Utilities of Game Models for Cluster 1 18 Table 5: Average Expected Utilities of Game Models for Cluster 2 19 Table 6: Average Expected Utilities of Game Models for Cluster 3 20 Table 7: Average Expected Utilities of Game Models for Cluster 4 21 Table 8: Average Expected Utilities of Game Models for 3 Gates 22 Table 9: Average Expected Utilities of Game Models for 6 Gates 23 Table 10: Average Expected Utilities of Game Models for 9 Gates 24 Table 11: Average Expected Utilities of Game Models for 12 Gates 25 Table 12: Average Expected Utilities of Game Models for 15 Gates 26 Table 13: Average Expected Utilities for PT Model 27 Table 14: Average Expected Utilities for PT-Attract Model 28 Table 15: Average Expected Utilities for COBRA (α = 0.15) Model 29 Table 16: Average Expected Utilities for COBRA (α = 0.5) Model 30 Table 17: Average Expected Utilities for DOBSS Model 31 Table 18: Average Expected Utilities for QRE (λ = 0.45) Model 32 Table 19: Average Expected Utilities for QRE (λ = 0.76) Model 33 Table 20: Time Weighted Average Expected Utilities against No. of Gates for Cluster 1 35 |
