Search arXivSearch

arXiv · 2110.12568

Analyzing a Complex Game for the South China Sea Fishing Dispute using Response Surface Methodologies

Abstract

The South China Sea (SCS) is one of the most economically valuable resources on the planet, and as such has become a source of territorial disputes between its bordering nations. Among other things, states compete to harvest the multitude of fish species in the SCS. In an effort to gain a competitive advantage states have turned to increased maritime patrols, as well as the use of "maritime militias," which are fishermen armed with martial assets to resist the influence of patrols. This conflict suggests a game of strategic resource allocation where states allocate patrols intelligently to earn the greatest possible utility. The game, however, is quite computationally challenging when considering its size (there are several distinct fisheries in the SCS), the nonlinear nature of biomass growth, and the influence of patrol allocations on costs imposed on fishermen. Further, uncertainty in player behavior attributed to modeling error requires a robust analysis to fully capture the dispute's dynamics. To model such a complex scenario, this paper employs a response surface methodology to assess optimal patrolling strategies and their impact on realized utilities. The methodology developed successfully finds strategies which are more robust to behavioral uncertainty than a more straight-forward method.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Michael Macgregor Perry. 2021-12-13. Analyzing a Complex Game for the South China Sea Fishing Dispute using Response Surface Methodologies. https://arxiv.org/abs/2110.12568

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

The time interpretation of expected utility theory

Economic models often maximise expectation values of wealth or utility. In non-ergodic settings, these can differ from time-averages, so that maximising expected outcomes need not maximise -- and can systematically reduce -- long-run wealth or utility. Ergodicity economics highlights this problem and models individual agents as maximising wealth in the long run, known as growth optimality. Two instances where expected utility maximisation maps to growth optimality are known: linear utility does this for additive wealth dynamics; and logarithmic utility for multiplicative wealth dynamics. Here we show that the mapping holds more generally when the utility function coincides with the ergodicity transformation in the growth optimal model. This mapping offers a theoretical basis for choosing utility functions and suggests the testable hypothesis that wealth dynamics are predictive of risk preferences.

econ.GN

Monetary Regimes and Trade before the Classical Gold Standard: Evidence from the Latin Monetary Union

This paper reexamines the trade effects of the Latin Monetary Union (LMU), a 19th century agreement to standardize gold and silver coinage among several European countries. The LMU provides a useful setting for studying whether monetary arrangements fostered trade before the classical gold standard, when gold, silver, bimetallic, and paper regimes coexisted. Because some countries already shared other monetary standards, treating all non-member pairs as a single control group mixes pairs with and without alternative forms of monetary coordination. I classify pairs by standard and estimate the LMU effect relative to pairs without a common standard, bringing the comparison closer to those used in the literature on the gold standard and contemporary currency unions. The results suggest that the LMU increased trade between its members by approximately 30\% during its early years, when bimetallism was still credible. These effects subsequently faded, converging to zero by the end of the 1870s. More broadly, these findings also highlight the importance of accounting for the existing monetary regimes when estimating the trade effects of other international policies.

econ.GN

Access to Live AI Advice and Behavior Under Risk: An Incentivized Experiment

Generative AI has become an everyday advisor, and the systems people consult are live and interactive, not pre-scripted. We ask whether access to such a system changes behavior under risk. In an incentivized experiment (N = 158), participants made lottery choices with an optional decision aid presented as a conventional pre-written tool, a live one-shot AI, or a live interactive AI they could query, with information format held equivalent across conditions. Risk preferences are elicited via DOSE. We find no evidence that access to a live AI advisor changes risk aversion.

econ.GN