This dissertation demonstrates, in a non-semantic information-theoretic framework,
how the principles of \maximisation of relevant information" and \information parsimony"
can guide the adaptation of an agent towards agent-agent interaction. Central
to this thesis is the concept of digested information; I argue that an agent is intrinsically
motivated to a.) process the relevant information in its environment and b.) display this
information in its own actions. From the perspective of similar agents, who require similar
information, this di erentiates other agents from the rest of the environment, by virtue of
the information they provide. This provides an informational incentive to observe other
agents and integrate their information into one's own decision making process.
This process is formalized in the framework of information theory, which allows for a
quantitative treatment of the resulting e ects, speci cally how the digested information
of an agent is in
uenced by several factors, such as the agent's performance and the
integrated information of other agents.
Two speci c phenomena based on information maximisation arise in this thesis. One is
ocking behaviour similar to boids that results when agents are searching for a location in a
girdworld and integrated the information in other agent's actions via Bayes' Theorem. The
other is an e ect where integrating information from too many agents becomes detrimental
to an agent's performance, for which several explanations are provided
