Albarracin, M.; Ramstead, M.; Pitliya, R.J.; Hipolito, I.; Da Costa, L.; Raffa, M.; Constant, A.; Manski, S.G. Sustainability under Active Inference. Systems 2024, 12, 163, doi:10.3390/systems12050163.
Albarracin, M.; Ramstead, M.; Pitliya, R.J.; Hipolito, I.; Da Costa, L.; Raffa, M.; Constant, A.; Manski, S.G. Sustainability under Active Inference. Systems 2024, 12, 163, doi:10.3390/systems12050163.
Albarracin, M.; Ramstead, M.; Pitliya, R.J.; Hipolito, I.; Da Costa, L.; Raffa, M.; Constant, A.; Manski, S.G. Sustainability under Active Inference. Systems 2024, 12, 163, doi:10.3390/systems12050163.
Albarracin, M.; Ramstead, M.; Pitliya, R.J.; Hipolito, I.; Da Costa, L.; Raffa, M.; Constant, A.; Manski, S.G. Sustainability under Active Inference. Systems 2024, 12, 163, doi:10.3390/systems12050163.
Abstract
In this paper we explore the known connection among sustainability, resilience, and well-being within the framework of active inference. Initially, we revisit how the notions of well-being and resilience intersect within active inference before defining sustainability. We adopt a holistic concept of sustainability denoting the enduring capacity to meet needs over time without depleting crucial resources. It extends beyond material wealth to encompass community networks, labor, and knowledge. Using the Free Energy Principle, we can emphasize the role of fostering resource renewal, harmonious system-entity exchanges, and practices that encourage self-organization and resilience as pathways to achieving sustainability, both in an agent and in collectives. We start by connecting Active Inference with well-being, building on exsiting work. We then attempt to link resilience with sustainability, asserting that resilience alone is insufficient for sustainable outcomes. While crucial for absorbing shocks and stresses, resilience must be intrinsically linked with sustainability to ensure that adaptive capacities do not merely perpetuate existing vulnerabilities. Rather, it should facilitate transformative processes that address the root causes of unsustainability. Sustainability, therefore, must manifest across extended timescales and all system strata, from individual components to the broader system, to uphold ecological integrity, economic stability, and social well-being. We explain how sustainability manifests at the level of an agent, and then at the level of collectives and systems. To model and quantify the interdependencies between resources and their impact on overall system sustainability, we introduce the application of network theory and dynamical systems theory. We emphasize the optimization of precision or learning rates through the active inference framework, advocating for an approach that fosters the elastic and plastic resilience necessary for long-term sustainability and abundance.
Keywords
active inference; sustainability; systems ; elasticity ; plasticity ; resilience;
Subject
Environmental and Earth Sciences, Sustainable Science and Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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