Semantic Information in a Model of Resource Gathering Agents
Damian R. Sowinski, Jonathan Carroll-Nellenback, Robert N. Markwick, Jordi Piñero, Marcelo Gleiser, Artemy Kolchinsky, Gourab Ghoshal, and Adam Frank
PRX Life 1, 023003 – Published 17 October 2023
Abstract
We explore the application of a theory of semantic information to the well-motivated problem of resource foraging. Semantic information is defined as the subset of correlations, which is here measured via the transfer entropy, between agent A and environment E that is necessary for the agent to maintain its viability V. Viability, in turn, is endogenously defined as opposed to the use of exogenous quantities like utility functions. In our model, the forager's movements are determined by its ability to measure, via a sensor, the presence of an individual unit of resource, while the viability function is its expected lifetime. Through “interventions”—scrambling the correlations between agent and environment by noising the sensor—we demonstrate the presence of a critical value of the noise parameter, ηc, above which the forager's expected lifetime is dramatically reduced. On the other hand, for η<ηc there is little to no effect on its ability to survive. We refer to this boundary as the semantic threshold, quantifying the subset of agent-environment correlations that the agent actually needs to maintain its desired state of staying alive. Each bit of information affects the agent's ability to persist both above and below the semantic threshold. Modeling the viability curve and its semantic threshold via forager and/or environment parameters, we show how the correlations are instantiated. Our work demonstrates the successful application of semantic information to a well-known agent-based model of biological and ecological interest. Additionally, we demonstrate that the concept of semantic thresholds may prove useful for understanding the role information plays in allowing systems to become autonomous agents.
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