We have constructed a model of the evolution of virtual organisms. In the initial version of the model, the "organisms" are boolean networks, whose structure is specified by a "genome" which is heritable but subject to mutation. Each network is stepped through a "life cycle" in which the "task" is to generate, as closely as possible, a target function specified by the investigator. Organisms are selected for their accuracy in carrying out the task. This resulted in the evolution of organisms that were highly effective at simulating the target function. When organisms were subjected to environmental perturbation, in the form of injected, numerical noise, they could, under some circumstances, adapt by developing the ability to exclude the noise. However, we unexpectedly discovered that, under other cirumstances, organisms would adapt by incorporating extrraneous and irrelevant features of the noise into their own structure, such that it became enmeshed in the function of the organism and necessary for its function. This process, which we dubbed "noise imprinting" appears to be analogous to many situations in which extraneous elements are entrained into human culture during the process of cultural evolution. In the current project period, we have parallelized the model and implemented it on Beowulf clusters (Biowulf at NIH Bethesda, and a dedicated 48-processor cluster in our lab) increasing computational power by 2-3 orders of magnitude. Using this added power, we are constructing a model of the co-evolution of "organisms" and "memes" ("cultural" elements) the latter of which replicate by spreading among the organisms and act as "software" to control the organisms'interactions with the environment, analogous to the co-evolution of the human genome and human culture. We hypothesize that this two level evolutionary process may have consequences analogous to "group selection" among the organisms. We speculate that the evolving memes may divide into "rational" ones that act in the short term on the basis of empirical infromation from the environment and "mythological" ones that embody permanent, non-observable "truths" about the evolutionary process itself that are of value in supporting survival of the organisms over multi-generational time scales. This might provide an analog of the "scientific" and "religious" cultural elements that co-exist in all human societies. We are giving particular attention to the kinds of co-evolutionary interactions that can occur in tightly coupled pairs of organisms, such as host/commensal pairs and the analogous relationship between genes and memes. Since organisms of such a pair have separate reproductive cycles, despite their close interdependence, so they have the "free will" to evolve in ways that "renegotiate" their relationship. We are looking to see if these transformations, which seem to be a useful model for many of the shifts in power and dominance that occur in human culture, are manifest in the computational simulations. Of particular interest is the possibility that the co-evolution of genes and culture may drive biological evolution in the direction of longer post-reproductive life span (because the teaching of the culture cannot be completed within one biological reproductive cycle). We will look for similar phenomena in the co-evolution models. Since the previous report we have developed an additional simulation model to study specifically the way in which irrational risk-taking evolves. In a stochastic model of natural selection, organisms that "gambled" increasing the variance of their fitness without increasing (or even decreasing)its avereage value were found to be at a disadvantage. However, when the effects of cultural or other epigenetic inheritance were included in the model, that pattern shifted dramatically, so that risk-taking behavior of no immediate benefit to the organism was nevertheless strongly sselected over multiple generations. The original version of this model concerned asexual organisms (or equivalently, traits coded on the Y chromosome). The risk model is now being extended to full sexual reproduction, and we are trying to see if the same generic effect of "cultural" evolution exists in the abstract boolean network model. During the current project period we have also begun to explore an additional hypothesis concerning the evolutionary role of the "Tragedy of the Commons" in which competition among rational actors for a limited resource may lead to a situation which is optimal for none of them. A very simple (but real-world relevant) model of fishermen trying to maximize their individual catches was found to lead to a steady state of fish depletion. Despite being a competitive equilibrium of the "hidden hand" this state is inferior in every regard (total yield, number of fish, number of fisherman) to a regulated regime -- i.e. all players could benefit if the fishermen "voluntarily" restricted their catch. Analysis of the equations shows that this situation depends on the fact that the scarce resource -- fish -- is a living (i.e. reproducing) species. Since this situation exists in nature, one might expect that evolution would take advantage of this opportunity for optimization. A non-social species in which each animal restricts his foraging would not be evolutionarily stable -- a cheater could do better. However, if individuals take ownership of parts of the resource by defending territories, then an optimal state could be stable. This suggests that the common evolution of territoriality or hierarchy (pecking order) may be as a mechanism to provide "stewardship" of living resources. A similar process might exist in cultural evolution, where complicated forms of territoriality and hierarchy are the norm. This leads to paradoxes, such as the possibility that the stability of feudal forms of governance/economy may reflect a better ability -- in a long-term steady state -- to husband resources for the benefit of all individuals than the more liberal free competition which is manifestly more successful in an era of growth. Further analysis of this model system may lead to collaborations with social scientists.