Language Evolution and Computation Bibliography

A trait is of adaptive value if it confers a fitness advantage to its possessor. Thus adaptivness is an ahistorical identification of a trait affording some selective advantage to an agent within some particular environment. In results reported here we identify a trait within natural language discourse as having adaptive value by computing a trait/fitness covariance; the possession of the trait correlates with the replication success of the trait's possessor. We show that the trait covaries with fitness across multiple unrelated discursive groups. In our analysis the trait in question is a particular statistically derived word?n? context, that is, a word set. Variation of the word?sage is measured as the relative presence of the word set within a particular text, that is, the percentage of the text devoted to this set of words. Fitness is measured as the rate in which the text is responded to, or replicates, within an online environment. Thus we are studying the micro?volutionary dynamics of natural language discourse.

A new microevolutionary theory of complex design within language is pro- posed. Experiments were carried out that support the theory that complex functional design --- adaptive complexity --- accumulates due to the evolu- tionary algorithm at the simplest levels within human natural language. A large software system was developed which identifies and tracks evolution- ary dynamics within text discourse. With this system hundreds of examples of activity suggesting evolutionary significance were distilled from a text collection of many millions of words.

Research contributions include: (1) An active replicator model of micro- evolutionary dynamics within natural language, (2) methods to distill active replicators offering evidence of evolutionary processes in action and at multiple linguistic levels (lexical, lexical co-occurrence, lexico-syntac- tic, and syntactic), (3) a demonstration that language evolution and organic evolution are both examples of a single over-arching evolutionary algo- rithm, (4) a set of tools to comparatively study language over time, and (5) methods to materially improve text retrieval.

The use of biological models and metaphors in studies of culture has a long and checkered history. While there are many superficial similarities between biological and cultural evolution, attempts to pin down such analogies have not been wholly successful. One limiting factor may be a lack of empirical evidence that the basic assumptions of the evolutionary model are met within a cultural system. We argue that a focus on the detection and description of the units of selection is an essential first step in constructing any evolutionary model. In this paper we outline the necessary connection between units of selection and evolution, describe the properties of a unit of selection, and introduce an empirical method for the detection of putative units of selection in a model cultural system: discourse within NetNews, a discussion system on the Internet.