Digested Information as an Information Theoretic Motivation for Social Interaction
Christoph Salge, Daniel Polani · Journal of Artificial Societies and Social Simulation · 2011
Within a universal agent-world interaction framework, based on Information Theory and Causal Bayesian Networks, we demonstrate how every agent that needs to acquire relevant information in regard to its strategy selection will automatically inject part of this information back into the environment. We introduce the concept of 'Digested Information' which both quantifies, and explains this phenomenon. Based on the properties of digested information, especially the high density of relevant information in other agents actions, we outline how this could motivate the development of low level social interaction mechanisms, such as the ability to detect other agents.