Cataloged from PDF version of article.A genetic algorithm is introduced to search for optimal policies in the presence of\ud knowledge spillovers and local pollution in a dynamic North/South trade game. Noncooperative\ud trade compounds inefficiencies stemming from externalities. Cooperative\ud trade policies are efficient and yet not credible. Short of a joint maximization of the global\ud welfare, transfer of knowledge remains as a viable route to improve world welfare.\ud 0 1998 Elsevier Science B.V. All rights reserved

Trade in natural resources is construed as a dynamic game between North and South. Policies that promote growth in the North also cause knowledge spillovers and transboundary pollution in the South. Cooperative and noncooperative Nash equilibria of this strategic trade game are simulated under various scenarios by parallel genetic algorithms to highlight the distortions in the growth/pollution trade-off. Absent cooperation, both regions benefit when North simultaneously cuts waste and increases knowledge spillovers, impelling South to reciprocate by lower resource prices.

This paper develops a method to compute the Stackelberg equilibria in sequential games. We construct a normal form game which is interactively played by an artiÿcially intelligent leader, GA L , and a follower, GA F. The leader is a genetic algorithm breeding a population of potential actions to better anticipate the follower's reaction. The follower is also a genetic algorithm training on-line a suitable neural network to evolve a population of rules to respond to any move in the leader's action space. When GAs repeatedly play this game updating each other synchronously, populations converge to the Stackelberg equilibrium of the sequential game. We provide numerical examples attesting to the e ciency of the algorithm.

This paper examines linkages between international trade, environmental degradation, and economic growth in a dynamic North-South trade game. Using a neoclassical production function subject to an endogenously improving technology, North produces manufactured goods by employing labor, capital, and a natural resource that it imports from South. South extracts the resource using raw labor, in the process generating local pollution.We study optimal regional policies in the presence of local pollution and technology spillovers from North to South under both non-cooperative and cooperative modes of trade. Non-cooperative trade is inefficient due to stock externalities. Cooperative trade policies are efficient and yet do not benefit North. Both regions gain from improved productivity in North and faster knowledge diffusion to South regardless of the trading regime.r oie_800 906..926

Cataloged from PDF version of article.This paper shows the computational benefits of a game theoretic approach to optimization of high dimensional control problems. A dynamic noncooperative game framework is adopted to partition the control space and to search the optimum as the equilibrium of a k-person dynamic game played by k-parallel genetic algorithms. When there are multiple inputs, we delegate control authority over a set of control variables exclusively to one player so that k artificially intelligent players explore and communicate to learn the global optimum as the Nash equilibrium. In the case of a single input, each player's decision authority becomes active on exclusive sets of dates-so that k GAs construct the optimal control trajectory as the equilibrium of evolving best-to-date responses. Sample problems are provided to demonstrate the gains in computational speed and accuracy. (C) 2000 Elsevier Science B.V. All rights reserved