scholarly journals An oscillating tragedy of the commons in replicator dynamics with game-environment feedback

2016 ◽  
Vol 113 (47) ◽  
pp. E7518-E7525 ◽  
Author(s):  
Joshua S. Weitz ◽  
Ceyhun Eksin ◽  
Keith Paarporn ◽  
Sam P. Brown ◽  
William C. Ratcliff
Keyword(s):  
Replicator Dynamics ◽  
Evolutionary Game ◽  
Tragedy Of The Commons ◽  
Individual Behavior ◽  
Global Maximum ◽  
Rational Choices ◽  
The Commons ◽  
Game Theoretic ◽  
Individual Actions ◽  
Game Environment

A tragedy of the commons occurs when individuals take actions to maximize their payoffs even as their combined payoff is less than the global maximum had the players coordinated. The originating example is that of overgrazing of common pasture lands. In game-theoretic treatments of this example, there is rarely consideration of how individual behavior subsequently modifies the commons and associated payoffs. Here, we generalize evolutionary game theory by proposing a class of replicator dynamics with feedback-evolving games in which environment-dependent payoffs and strategies coevolve. We initially apply our formulation to a system in which the payoffs favor unilateral defection and cooperation, given replete and depleted environments, respectively. Using this approach, we identify and characterize a class of dynamics: an oscillatory tragedy of the commons in which the system cycles between deplete and replete environmental states and cooperation and defection behavior states. We generalize the approach to consider outcomes given all possible rational choices of individual behavior in the depleted state when defection is favored in the replete state. In so doing, we find that incentivizing cooperation when others defect in the depleted state is necessary to avert the tragedy of the commons. In closing, we propose directions for the study of control and influence in games in which individual actions exert a substantive effect on the environmental state.

scholarly journals An oscillating tragedy of the commons in replicator dynamics with game-environment feedback

2016 ◽  
Author(s):  
Joshua S. Weitz ◽  
Ceyhun Eksin ◽  
Keith Paarporn ◽  
Sam P. Brown ◽  
William C. Ratcliff
Keyword(s):  
Replicator Dynamics ◽  
Evolutionary Game ◽  
Tragedy Of The Commons ◽  
Individual Behavior ◽  
Global Maximum ◽  
New Class ◽  
Rational Choices ◽  
The Commons ◽  
Game Theoretic ◽  
Game Environment

A tragedy of the commons occurs when individuals take actions to maximize their payoffs even as their combined payoff is less than the global maximum had the players coordinated. The originating example is that of over-grazing of common pasture lands. In game theoretic treatments of this example there is rarely consideration of how individual behavior subsequently modifies the commons and associated payoffs. Here, we generalize evolutionary game theory by proposing a class of replicator dynamics with feedback-evolving games in which environment-dependent payoffs and strategies coevolve. We initially apply our formulation to a system in which the payoffs favor unilateral defection and cooperation, given replete and depleted environments respectively. Using this approach we identify and characterize a new class of dynamics: an oscillatory tragedy of the commons in which the system cycles between deplete and replete environmental states and cooperation and defection behavior states. We generalize the approach to consider outcomes given all possible rational choices of individual behavior in the depleted state when defection is favored in the replete state. In so doing we find that incentivizing cooperation when others defect in the depleted state is necessary to avert the tragedy of the commons. In closing, we propose new directions for the study of control and influence in games in which individual actions exert a substantive effect on the environmental state.

scholarly journals eGAP: An Evolutionary Game Theoretic Approach to Random Forest Pruning

2020 ◽  
Vol 4 (4) ◽  
pp. 37
Author(s):  
Khaled Fawagreh ◽  
Mohamed Medhat Gaber
Keyword(s):  
Random Forest ◽  
Replicator Dynamics ◽  
Evolutionary Game ◽  
Theoretic Approach ◽  
Healthcare Applications ◽  
Healthcare Data ◽  
Smart Healthcare ◽  
Game Theoretic ◽  
Game Theoretic Approach

To make healthcare available and easily accessible, the Internet of Things (IoT), which paved the way to the construction of smart cities, marked the birth of many smart applications in numerous areas, including healthcare. As a result, smart healthcare applications have been and are being developed to provide, using mobile and electronic technology, higher diagnosis quality of the diseases, better treatment of the patients, and improved quality of lives. Since smart healthcare applications that are mainly concerned with the prediction of healthcare data (like diseases for example) rely on predictive healthcare data analytics, it is imperative for such predictive healthcare data analytics to be as accurate as possible. In this paper, we will exploit supervised machine learning methods in classification and regression to improve the performance of the traditional Random Forest on healthcare datasets, both in terms of accuracy and classification/regression speed, in order to produce an effective and efficient smart healthcare application, which we have termed eGAP. eGAP uses the evolutionary game theoretic approach replicator dynamics to evolve a Random Forest ensemble. Trees of high resemblance in an initial Random Forest are clustered, and then clusters grow and shrink by adding and removing trees using replicator dynamics, according to the predictive accuracy of each subforest represented by a cluster of trees. All clusters have an initial number of trees that is equal to the number of trees in the smallest cluster. Cluster growth is performed using trees that are not initially sampled. The speed and accuracy of the proposed method have been demonstrated by an experimental study on 10 classification and 10 regression medical datasets.

scholarly journals The world's biomes and primary production as a triple tragedy of the commons foraging game played among plants

2016 ◽  
Vol 283 (1842) ◽  
pp. 20161993 ◽  
Author(s):  
Gordon G. McNickle ◽  
Miquel A. Gonzalez-Meler ◽  
Douglas J. Lynch ◽  
Jennifer L. Baltzer ◽  
Joel S. Brown
Keyword(s):  
Primary Production ◽  
Tragedy Of The Commons ◽  
Plant Production ◽  
Root Production ◽  
Theoretic Model ◽  
Theoretic Approach ◽  
Evolutionarily Stable Strategies ◽  
The Commons ◽  
Game Theoretic ◽  
Tissue Production

Plants appear to produce an excess of leaves, stems and roots beyond what would provide the most efficient harvest of available resources. One way to understand this overproduction of tissues is that excess tissue production provides a competitive advantage. Game theoretic models predict overproduction of all tissues compared with non-game theoretic models because they explicitly account for this indirect competitive benefit. Here, we present a simple game theoretic model of plants simultaneously competing to harvest carbon and nitrogen. In the model, a plant's fitness is influenced by its own leaf, stem and root production, and the tissue production of others, which produces a triple tragedy of the commons. Our model predicts (i) absolute net primary production when compared with two independent global datasets; (ii) the allocation relationships to leaf, stem and root tissues in one dataset; (iii) the global distribution of biome types and the plant functional types found within each biome; and (iv) ecosystem responses to nitrogen or carbon fertilization. Our game theoretic approach removes the need to define allocation or vegetation type a priori but instead lets these emerge from the model as evolutionarily stable strategies. We believe this to be the simplest possible model that can describe plant production.

scholarly journals Some plants don’t play games: An ideal free distribution explains the root production of plants that do not engage in a tragedy of the commons game.

2014 ◽  
Author(s):  
Gordon McNickle ◽  
Joel S Brown
Keyword(s):  
Seed Yield ◽  
Ideal Free Distribution ◽  
Tragedy Of The Commons ◽  
Stable Strategy ◽  
Free Distribution ◽  
Root Allocation ◽  
The Commons ◽  
Game Theoretic ◽  
Soil Volume ◽  
Ideal Free

1. Game theoretic models that seek to predict the most competitive strategy plants use for competition in soil are clear; they generally predict that over-proliferation of roots is the only evolutionarily stable strategy. However, empirical studies are equally clear that not all plants employ this strategy of over-proliferation of roots. Here, our goal was to develop and test an alternative non-game theoretic model that can be used to develop alternative hypotheses for plants that do not appear to play games. 2. The model is similar to previous models, but does not use a game theoretic optimization criterion. Instead, plants use only nutrient availability to select a root allocation strategy, ignoring neighbours. To test the model we compare root allocation and seed yield of plants grown either alone or with neighbours. 3. The model predicted plants that do not sense neighbours (or ignore neighbours) should allocate roots relative to resource availability following an ideal free distribution. This means that if a soil volume of quality R contains x roots, then a soil volume of quality R/n will contain x/n roots. The experimental data were consistent with this prediction. That is, plants grown with 1.2g of slow release fertilizer resources produced 0.043 g of roots, while plants grown with neighbours, or plants grown with half as much fertilizer produced half as much root mass (0.026g, and 0.24g respectively). Seed yield followed a similar pattern. 4. This model presents an alternative predictive framework for those plant species that do not seem to play a tragedy of the commons game for belowground competition. 5. Synthesis: It remains unclear why some plants do not engage in belowground games for competition. Models suggest over-proliferation is an unbeatable evolutionary stable strategy, yet plants that do not play the game apparently coexist with plants that do. We suggest that a greater understanding of trade-offs among traits that are important for other biotic interactions (above-ground competition, enemy defence, mutualisms) will lead to a greater understanding of why some species over-proliferate roots when in competition but other species do not.

Generalized Replicator Dynamics as a Model of Specialization and Diversity in Societies

1998 ◽  
Vol 01 (04) ◽  
pp. 325-359 ◽  
Author(s):  
Vivek S. Borkar ◽  
Sanjay Jain ◽  
Govindan Rangarajan
Keyword(s):  
Mixed Strategy ◽  
Replicator Dynamics ◽  
Pure Strategy ◽  
Evolutionary Game ◽  
Payoff Matrix ◽  
Theoretic Model ◽  
Final States ◽  
Game Theoretic ◽  
Game Theoretic Model ◽  
Pure Strategies

We consider a generalization of replicator dynamics as a non-cooperative evolutionary game-theoretic model of a community of N agents. All agents update their individual mixed strategy profiles to increase their total payoff from the rest of the community. The properties of attractors in this dynamics are studied. Evidence is presented that under certain conditions the typical attractors of the system are corners of state space where each agent has specialized to a pure strategy, and/or the community exhibits diversity, i.e., all strategies are represented in the final states. The model suggests that new pure strategies whose payoff matrix elements satisfy suitable inequalities with respect to the existing ones can destabilize existing attractors if N is sufficiently large, and be regarded as innovations that enhance the diversity of the community.

scholarly journals Inspection—Corruption Game of Illegal Logging and Other Violations: Generalized Evolutionary Approach

Mathematics ◽  
2021 ◽  
Vol 9 (14) ◽  
pp. 1619
Author(s):  
Vassili N. Kolokoltsov
Keyword(s):  
Tax Evasion ◽  
Replicator Dynamics ◽  
Evolutionary Game ◽  
Efficient Frontier ◽  
Point Of View ◽  
Quadratic Growth ◽  
Illegal Logging ◽  
Major Player ◽  
Game Theoretic ◽  
Evolutionary Point

Games of inspection and corruption are well developed in the game-theoretic literature. However, there are only a few publications that approach these problems from the evolutionary point of view. In previous papers of this author, a generalization of the replicator dynamics of the evolutionary game theory was suggested for inspection modeling, namely the pressure and resistance framework, where a large pool of small players plays against a distinguished major player and evolves according to certain myopic rules. In this paper, we develop this approach further in a setting of the two-level hierarchy, where a local inspector can be corrupted and is further controlled by the higher authority (thus combining the modeling of inspection and corruption in a unifying setting). Mathematical novelty arising in this investigation involves the analysis of the generalized replicator dynamics (or kinetic equation) with switching, which occurs on the “efficient frontier of corruption”. We try to avoid parameters that are difficult to observe or measure, leading to some clear practical consequences. We prove a result that can be called the “principle of quadratic fines”: We show that if the fine for violations (both for criminal businesses and corrupted inspectors) is proportional to the level of violations, the stable rest points of the dynamics support the maximal possible level of both corruption and violation. The situation changes if a convex fine is introduced. In particular, starting from the quadratic growth of the fine function, one can effectively control the level of violations. Concrete settings that we have in mind are illegal logging, the sales of products with substandard quality, and tax evasion.

scholarly journals The Tragedy of the Commons from a Game-Theoretic Perspective

2012 ◽  
Vol 4 (8) ◽  
pp. 1776-1786 ◽  
Author(s):  
Florian K. Diekert
Keyword(s):  
Tragedy Of The Commons ◽  
The Commons ◽  
Game Theoretic

scholarly journals The Tragedy of the Commons as a Prisoner’s Dilemma. Its Relevance for Sustainability Games

2021 ◽  
Vol 13 (15) ◽  
pp. 8125
Author(s):  
Alessio Carrozzo Magli ◽  
Pompeo Della Posta ◽  
Piero Manfredi
Keyword(s):  
Prisoner's Dilemma ◽  
Global Climate ◽  
Prisoner’S Dilemma ◽  
Tragedy Of The Commons ◽  
Policy Interventions ◽  
The Commons ◽  
Game Theoretic ◽  
Sustainability Policy ◽  
Harmful Effects ◽  
Ultimate Nature

In the current battle for sustainability and climate, understanding the nature of sustainability games is of paramount importance, especially to inform appropriate policy actions to contrast the harmful effects of global climate change. Relatedly, there is no consensus in the literature on the proper game-theoretic representation of the so-called Tragedy of the Commons. A number of contributions have questioned the prisoner’s dilemma as an appropriate framework. In this work, we provide a representation that reconciles these two positions, confirming the ultimate nature of the Tragedy as a prisoner’s dilemma, rather than a coordination issue, and discuss the ensuing implications for sustainability policy interventions.

"Once? No. Twenty times? Sure!" Repeated decisions and uncertainty in the tragedy of the commons

2014 ◽  
Author(s):  
David J. Hardisty ◽  
Howard Kunreuther ◽  
David H. Krantz ◽  
Poonam Arora
Keyword(s):  
Tragedy Of The Commons ◽  
The Commons
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