Adaptive behavior might emerge more generally in open thermodynamic systems as a result of physical agents acting with some or all of the systems’ degrees of freedom so as to maximize the overall diversity of accessible future paths of their worlds (causal entropic forcing).
In practice, such agents might estimate causal entropic forces through internal Monte Carlo sampling of future histories generated from learned models of their world. Such behavior would then ensure their uniform aptitude for adaptiveness to future change due to interactions with the environment, conferring a potential survival advantage, to the extent permitted by their strength (parametrized by a causal path temperature, Tc) and their ability to anticipate the future (parametrized by a causal time horizon, ).

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