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Why Developing Simulation Capabilities Promotes Sustainable Adaptation to Climate Change

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Artificial Intelligence in HCI (HCII 2021)

Abstract

Simulations of social processes are a special category of interactions between humans and computers, characterized by the modeling through the latter of the behavior of the former. This paper proposes a framework for studying the development of simulation capabilities by society, as part of an ongoing process of adaptation by complex social systems against a more challenging environment. We begin by discussing the characteristics that the capability to simulate social systems confers in terms of increased effectiveness of the decision-making process of a society. Then, by framing this increased effectiveness as a problem of increased computational capacity by an intelligent agent, we describe the impact that this has on the fitness of an agent that is adapting to a changing environment. We thus provide a mathematical formalization for studying the development of computational sociology in terms of adaptive fitness. This formalization lets us draw the interesting conclusion that, if the adapting system records a decrease in its fitness over its recent past, the formulation of adapting decisions becomes an increasingly more self-referential problem. That is to say, it depends increasingly more on the computation of the outcome of the past actions of the agent, and increasingly less on the behavior of the environment around it. This promotes the theoretical generalization that the development of simulation capabilities for adaptation increases the role that the agent has in determining the status of the agent’s world, and decreases the role that the environment has in the same process.

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Correspondence to Gabriele De Luca .

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De Luca, G., Lampoltshammer, T.J., Parven, S. (2021). Why Developing Simulation Capabilities Promotes Sustainable Adaptation to Climate Change. In: Degen, H., Ntoa, S. (eds) Artificial Intelligence in HCI. HCII 2021. Lecture Notes in Computer Science(), vol 12797. Springer, Cham. https://doi.org/10.1007/978-3-030-77772-2_32

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  • DOI: https://doi.org/10.1007/978-3-030-77772-2_32

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