An artificial life entertainment-software product called Creatures was released in Europe in late 1996 and in the United States and Japan in mid-1997. When installed on a domestic computer (PC or Macintosh), each Creatures CD-ROM creates a virtual world in which autonomous software agents exist. The agents, known as "norns", interact with the human user, with each other, and with objects in their virtual world. Each norn coordinates perception and action via its own modular recurrent neural network: Each network has Hebbian learning, plus diffuse modulation of activity via a "hormonal" system that is part of that norn's "biochemistry". Details of each norn's neural network and biochemistry are genetically specified, and norns can breed via sexual reproduction. In the reproduction process, genetic material may be mutated and may also be subjected to "gene duplications" that enable potentially unlimited increases in complexity of the norns' design. Over 500,000 Creatures CD-ROMS have now been sold. As each installed copy of Creatures can support 5 to 10 simultaneously existing individual norns, it seems reasonable to estimate that there are up to 5 million norns existing in the "cyberspace" provided by the global Creatures user community.

We make use of a set of text analysis tools, primarily based on Latent Semantic Indexing, to study the dynamics of memes on the Net. Our analysis discovers replicating memes within posts to the USENET News (or NetNews) system. We cluster the posts to NetNews into clouds within a conceptual sequence space; these clusters describe quasispecies. We then go on to study the pairwise interactions between these quasi-species by computing the cross-correlation between the interacting population's level of post activity. We analyze a particular corpus of posts to the soc.women newsgroup and argue that strong negative crosscorrelations are examples of competition between the quasi-species. We find that high levels of competition occur more frequently among quasi-species who exist within a narrow ecological niche. We note that this phenomena also occurs in natural ecologies. 1 Introduction Ideas do not exist in a vacuum. Neither does discourse, the interconnected ideas which make up conversatio...

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 anal-ogies 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 puta-tive units of selection in a model cultural system: discourse within Net-News, a discussion system on the Internet. “One of the most interesting things about Darwin’s explanation

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-in-context, that is, a word set. Variation of the word-usage 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-evolutionary dynamics of natural language discourse.

Defining the meme Dynamics of meme replication and spread Social structures Computer simulations of cultural evolution