PAWS: Game Theory Based Protection Assistant for Wildlife Security

This chapter introduces Protection Assistant for Wildlife Security (PAWS) (Yang, Ford, Tambe, & Lemieux, 2014) as a joint effort done by computer scientists, conservation researchers, and conservation practitioners from two nongovernmental organizations— Panthera, and Rimba. PAWS is a game theory based application to assist conservation agency officials in planning wildlife ranger patrols to prevent wildlife crime. Reducing risks to people and wildlife from wildlife crime ideally includes the combined effort of practitioners worldwide and researchers in many different disciplines; PAWS demonstrates the positive impact that research in computational game theory, an important topic within the field of Artificial Intelligence (AI), can have in assisting wildlife conservation agencies to prevent poaching. In recent deployment efforts, patrol planners mentioned that the routes generated by PAWS came close to an actual planner's routes, a promising sign that PAWS can suggest feasible routes and help reduce the significant burden of patrol planning.

[1]  W. A. Wagenaar.  Generation of random sequences by human subjects: A critical survey of literature. , 1972 .

[2]  Moses Makonjio Okello,et al.  Correlates of wildlife snaring patterns in Tsavo West National Park, Kenya , 2006 .

[3]  Milind Tambe,et al.  Robust Protection of Fisheries with COmPASS , 2014, AAAI.

[4]  Edward Opiyo Ouko.  Where , when and why are there elephant poaching hotspots in Kenya ? , 2013 .

[5]  Noa Agmon,et al.  Making the Most of Our Regrets: Regret-Based Solutions to Handle Payoff Uncertainty and Elicitation in Green Security Games , 2015, GameSec.

[6]  William D. Moreto.  To conserve and protect: examining law enforcement ranger culture and operations in Queen Elizabeth National Park, Uganda , 2013 .

[7]  Milind Tambe,et al.  Security and Game Theory: IRIS – A Tool for Strategic Security Allocation in Transportation Networks , 2011, AAMAS 2011.

[8]  Bo An,et al.  PROTECT: a deployed game theoretic system to protect the ports of the United States , 2012, AAMAS.

[9]  E. Stokes,et al.  Improving effectiveness of protection efforts in tiger source sites: Developing a framework for law enforcement monitoring using MIST. , 2010, Integrative zoology.

[10]  Milind Tambe,et al.  Optimal patrol strategy for protecting moving targets with multiple mobile resources , 2013, AAMAS.

[11]  Milind Tambe,et al.  When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing , 2015, IJCAI.

[12]  Amos Azaria,et al.  Analyzing the Effectiveness of Adversary Modeling in Security Games , 2013, AAAI.

[13]  Martyn Plummer,et al.  JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling , 2003 .

[14]  Milind Tambe,et al.  "A Game of Thrones": When Human Behavior Models Compete in Repeated Stackelberg Security Games , 2015, AAMAS.

[15]  Colin Camerer.  Behavioral Game Theory: Experiments in Strategic Interaction , 2003 .

[16]  Rong Yang,et al.  Adaptive resource allocation for wildlife protection against illegal poachers , 2014, AAMAS.

[17]  Milind Tambe,et al.  Comparing human behavior models in repeated Stackelberg security games: An extended study , 2016, Artif. Intell..

[18]  S. Pires,et al.  The illegal parrot trade in the neo-tropics: The relationship between poaching and illicit pet markets , 2012 .

[19]  M. Dufwenberg.  Game theory. , 2011, Wiley interdisciplinary reviews. Cognitive science.

[20]  Tomas Holmern,et al.  Local law enforcement and illegal bushmeat hunting outside the Serengeti National Park, Tanzania , 2007, Environmental Conservation.

[21]  Milind Tambe,et al.  Online planning for optimal protector strategies in resource conservation games , 2014, AAMAS.

[22]  Rong Yang,et al.  Scaling-up Security Games with Boundedly Rational Adversaries: A Cutting-plane Approach , 2013, IJCAI.

[23]  Milind Tambe,et al.  Security and Game Theory - Algorithms, Deployed Systems, Lessons Learned , 2011 .

[24]  Vincent Conitzer,et al.  Complexity of Computing Optimal Stackelberg Strategies in Security Resource Allocation Games , 2010, AAAI.

[25]  Sarit Kraus,et al.  Deployed ARMOR protection: the application of a game theoretic model for security at the Los Angeles International Airport , 2008, AAMAS.

[26]  Milind Tambe,et al.  Protecting Moving Targets with Multiple Mobile Resources , 2013, J. Artif. Intell. Res..

[27]  Milind Tambe,et al.  TRUSTS: Scheduling Randomized Patrols for Fare Inspection in Transit Systems , 2012, IAAI.