DOI: 10.5061/dryad.qjq2bvqnk
title: Code from: Efficiency traps beyond the climate crisis: Exploration-exploitation tradeoffs and rebound effects

description: These data are part of a data portal that accompanies the special issue
 ‘Climate change adaptation needs a science of culture,’ published in
 Philosophical Transactions of the Royal Society B in 2023. To access the
 data portal, please visit: https://doi.org/10.5061/dryad.bnzs7h4h4. This
 code represents a computational model investigating the dynamics of
 coupled and decoupled resource use and efficiency gains. It can be used to
 simulate the effects of exploration-exploitation strategies on efficiency,
 consumption and sustainability, considering different levels of direct and
 indirect rebound effects.  The model simulates a population of
 agents who make decisions on whether to explore or exploit a natural
 resource. These agents become more efficient over time based on their
 chosen strategy, affecting resource consumption. Different scenarios are
 considered, including various rebound effects, which influence how
 efficiency gains impact resource use. The key elements of the model
 include agents' uncertainty about the efficiency of their actions,
 the operationalization of efficiency as a reward, and the calculation of
 resource consumption based on efficiency gains and rebound effects. The
 model provides insights into how agents' decisions and resource use
 evolve over time under different conditions. This computational framework
 offers a valuable tool for exploring the complex dynamics of resource
 consumption and management in the face of environmental challenges. It can
 be applied to gain a deeper understanding of the Jevons Paradox and its
 implications for sustainable resource use.
description: This computational model simulates the dynamics of exploration
 and exploitation strategies within a population of agents. These agents
 make decisions on whether to explore new solutions or exploit existing
 ones, with a focus on maximizing efficiency. The model employs a N-armed
 bandit problem approach, where agents select actions to maximize
 efficiency gains. Efficiency is operationalized as a reward, and agents
 use sample means to estimate expected efficiency. A balance between
 exploration and exploitation is maintained through a probability-based
 algorithm. The code also encompasses resource domains, representing
 different resources and their dynamics, along with computations of
 resource consumption, existing resources, and sustainability indices. The
 simulations consider various parameter combinations to examine the
 model's behavior. Overall, the code serves as a
 tool for studying the interplay between exploration, exploitation,
 efficiency, and resource consumption within a population of agents across
 different scenarios, making it valuable for investigating the effects of
 rebound effects on resource consumption and sustainability. The
 simulations run a comprehensive set of parameter combinations to explore
 the model's behavior thoroughly.
description: # Code from: Efficiency traps beyond the climate crisis:
 Exploration-exploitation tradeoffs and rebound effects. Python scripts to
 run the model, as described in: Segovia-Martin J, Creutzig F, Winters J.
 2023 Efficiency traps beyond the climate crisis: exploration–exploitation
 tradeoffs and rebound effects. Phil. Trans. R. Soc. B 378: 20220405.
 https://doi.org/10.1098/rstb.2022.0405 The code and supplementary
 materials are all freely accessible at the following link:
 [https://github.com/School-of-Collective-Intelligence/Jevons-Paradox-and-Cultural-Evolution](https://github.com/School-of-Collective-Intelligence/Jevons-Paradox-and-Cultural-Evolution) The simulator can be accessed via the following links: [https://jevons-collectiveintelligence.pythonanywhere.com/](https://jevons-collectiveintelligence.pythonanywhere.com/) or [https://jsegoviamartin.pythonanywhere.com/](https://jsegoviamartin.pythonanywhere.com/) The DOI of this Dryad repository: [https://doi.org/10.5061/dryad.qjq2bvqnk](https://doi.org/10.5061/dryad.qjq2bvqnk) ##