Optimal control policies for evolutionary dynamics with environmental feedback
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2018 IEEE. We study a dynamical model of a population of cooperators and defectors whose actions have long-term consequences on environmental 'commons' - what we term the 'resource'. Cooperators contribute to restoring the resource whereas defectors degrade it. The population dynamics evolve according to a replicator equation coupled with an environmental state. Our goal is to identify methods of influencing the population with the objective of maximizing accumulation of the resource. In particular, we consider strategies that modify individual-level incentives. We then extend the model to include a public opinion state that imperfectly tracks the true environmental state, and study strategies that influence opinion. We formulate optimal control problems and solve them using numerical techniques to characterize locally optimal control policies for three problem formulations: 1) control of incentives, and control of opinions through 2) propaganda-like strategies and 3) awareness campaigns. We show numerically that the resulting controllers in all formulations achieve the objective, albeit with an unintended consequence. The resulting dynamics include cycles between low and high resource states - a regime termed an 'oscillating tragedy of the commons'. This outcome may have desirable average properties, but includes risks to resource depletion. Our findings suggest the need for new approaches to controlling population-environment dynamics.
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2018 IEEE Conference on Decision and Control (CDC)
