GMSE - Generalised Management Strategy Evaluation Simulator

Integrates game theory and ecological theory to construct social-ecological models that simulate the management of populations and stakeholder actions. These models build off of a previously developed management strategy evaluation (MSE) framework to simulate all aspects of management: population dynamics, manager observation of populations, manager decision making, and stakeholder responses to management decisions. The newly developed generalised management strategy evaluation (GMSE) framework uses genetic algorithms to mimic the decision-making process of managers and stakeholders under conditions of change, uncertainty, and conflict. Simulations can be run using gmse(), gmse_apply(), and gmse_gui() functions.

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adaptive-managementagricultural-modellingconflictconflict-resolutionconservationecological-modellingecological-modelsecologyfood-securitygame-theorygenetic-algorithmgenetic-algorithmsmanagement-decisionsmanagement-strategy-evaluationpopulation-modelsimulationwildlife-management

5.45 score 11 stars 172 scripts 209 downloads

resevol - Simulate Agricultural Production and Evolution of Pesticide Resistance

Simulates individual-based models of agricultural pest management and the evolution of pesticide resistance. Management occurs on a spatially explicit landscape that is divided into an arbitrary number of farms that can grow one of up to 10 crops and apply one of up to 10 pesticides. Pest genomes are modelled in a way that allows for any number of pest traits with an arbitrary covariance structure that is constructed using an evolutionary algorithm in the mine_gmatrix() function. Simulations are then run using the run_farm_sim() function. This package thereby allows for highly mechanistic social-ecological models of the evolution of pesticide resistance under different types of crop rotation and pesticide application regimes.

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4.78 score 3 stars 1 scripts 170 downloads

gamesGA - Genetic Algorithm for Sequential Symmetric Games

Finds adaptive strategies for sequential symmetric games using a genetic algorithm. Currently, any symmetric two by two matrix is allowed, and strategies can remember the history of an opponent's play from the previous three rounds of moves in iterated interactions between players. The genetic algorithm returns a list of adaptive strategies given payoffs, and the mean fitness of strategies in each generation.

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gamegame-theorygenetic-algorithmmachine-learningprisoner-dilemma-simulation

3.22 score 3 stars 11 scripts 207 downloads