Robust Protection of Fisheries with COmPASS

Fish stocks around the world are in danger from illegal fishing. In collaboration with the U.S. Coast Guard (USCG), we work to defend fisheries from illegal fisherman (henceforth called Lanchas) in the U.S. Gulf of Mexico. We have developed the COmPASS (Conservative Online Patrol ASSistant) system to design USCG patrols against the Lanchas. In this application, we face a population of Lanchas with heterogeneous behavior who fish frequently. We have some data about these Lanchas, but not enough to fit a statistical model. Previous security patrol assistants have focused on counterterrorism in one-shot games where adversaries are assumed to be perfectly rational, and much less data about their behavior is available. COmPASS is novel because: (i) it emphasizes environmental crime; (ii) it is based on a repeated Stackelberg game; (iii) it allows for bounded rationality of the Lanchas and it offers a robust approach against the heterogeneity of the Lancha population; and (iv) it can learn from sparse Lancha data. We report the effectiveness of COmPASS in the Gulf in our numerical experiments based on real fish data. The COmPASS system is to be tested by USCG.

[1]  Dimitris Bertsimas,et al.  Tractable stochastic analysis in high dimensions via robust optimization , 2012, Math. Program..

[2]  Laurent El Ghaoui,et al.  Robust Optimization , 2021, ICORES.

[3]  Gerald Tesauro,et al.  Playing repeated Stackelberg games with unknown opponents , 2012, AAMAS.

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

[5]  Dimitris Bertsimas,et al.  Robust game theory , 2006, Math. Program..

[6]  Vincent Conitzer.  Computing Game-Theoretic Solutions and Applications to Security , 2012, AAAI.

[7]  Roger B. Myerson,et al.  Game theory - Analysis of Conflict , 1991 .

[8]  V. Lobo,et al.  One dimensional Self-Organizing Maps to optimize marine patrol activities , 2005, Europe Oceans 2005.

[9]  Teofilo Ozuna,et al.  A Bioeconomic Assessment of Gulf of Mexico Red Snapper Management Policies , 2001 .

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

[11]  Harvey H. Millar,et al.  A model for fisheries patrol dispatch in the Canadian Atlantic offshore fishery , 2012 .

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

[13]  Juliane Hahn,et al.  Security And Game Theory Algorithms Deployed Systems Lessons Learned , 2016 .

[14]  Yevgeniy Vorobeychik,et al.  Computing Randomized Security Strategies in Networked Domains , 2011, Applied Adversarial Reasoning and Risk Modeling.

[15]  Olav Schram Stokke,et al.  Trade measures and the combat of IUU fishing: Institutional interplay and effective governance in the Northeast Atlantic , 2009 .

[16]  Milind Tambe,et al.  Optimal defender allocation for massive security games : A branch and price approach , 2010 .

[17]  Bertrand Le Gallic,et al.  An economic analysis of illegal, unreported and unregulated (IUU) fishing: Key drivers and possible solutions , 2006 .

[18]  T. Pitcher,et al.  Towards sustainability in world fisheries , 2002, Nature.

[19]  Ransom A. Myers,et al.  Shifting baselines and the decline of pelagic sharks in the Gulf of Mexico , 2004 .

[20]  R. Gibbons.  Game theory for applied economists , 1992 .

[21]  R. McKelvey,et al.  Quantal Response Equilibria for Normal Form Games , 1995 .

[22]  Sarit Kraus,et al.  Playing games for security: an efficient exact algorithm for solving Bayesian Stackelberg games , 2008, AAMAS.

[23]  G. Petrossian,et al.  The decision to engage in illegal fishing: an examination of situational factors in 54 countries , 2012 .

[24]  Randolph W. Hall,et al.  Discounted Robust Stochastic Games and an Application to Queueing Control , 2011, Oper. Res..

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