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We consider the problem of the evolution of a code within a structuredpopulation of agents. The agents try to maximise their information about theirenvironment by acquiring information from the outputs of other agents in thepopulation. A naive use of information-theoretic methods would assume thatevery agent knows how to "interpret" the information offered by other agents.However, this assumes that one "knows" which other agents one observes, andthus which code they use. In our model, however, we wish to preclude that: itis not clear which other agents an agent is observing, and the resulting usableinformation is therefore influenced by the universality of the code used and bywhich agents an agent is "listening" to. We further investigate whether anagent who does not directly perceive the environment can distinguish states byobserving other agents' outputs. For this purpose, we consider a population ofdifferent types of agents "talking" about different concepts, and try toextract new ones by considering their outputs only.

An informational study of the evolution of codes and of emerging concepts in populations of agents