Languages are transmitted from person to person and generation to generation via a process of iterated learning: people learn a language from other people who once learned that language themselves. We analyze the consequences of iterated learning for learning algorithms based on the principles of Bayesian inference, assuming that learners compute a posterior distribution over languages by combining a prior (representing their inductive biases) with the evidence provided by linguistic data. We show that when learners sample languages from this posterior (...) distribution, iterated learning converges to a distribution over languages that is determined entirely by the prior. Under these conditions, iterated learning is a form of Gibbs sampling, a widely-used Markov chain Monte Carlo algorithm. The consequences of iterated learning are more complicated when learners choose the language with maximum posterior probability, being affected by both the prior of the learners and the amount of information transmitted between generations. We show that in this case, iterated learning corresponds to another statistical inference algorithm, a variant of the expectation-maximization (EM) algorithm. These results clarify the role of iterated learning in explanations of linguistic universals and provide a formal connection between constraints on language acquisition and the languages that come to be spoken, suggesting that information transmitted via iterated learning will ultimately come to mirror the minds of the learners. (shrink)

Examining homology in biological and cultural evolution is of great importance in investigations of humanity. The proposal presented in the target article retains substantial methodological weaknesses in the identification and use of “cultural traits.” However, with refined toolkits and the incorporation of recent advances in evolutionary theory, this overall endeavor can result in substantial payoffs for biological and social scientists. (Published Online November 9 2006).

Mesoudi et al. overlook an illuminating parallel between cultural and biological evolution, namely, the existence in each realm of a continuum from intelligent, mindful evolution through to oblivious, mindless evolution. In addition, they underplay the independence of cultural fitness from biological fitness. The assumption that successful cultural traits enhance genetic fitness must be sidelined, as must the assumption that such traits will at least be considered worth having. (Published Online November 9 2006).

An effective restructuring of the social sciences around the evolutionary model requires that evolutionary theory has explanatory power with respect to the spread of cultural traits: The causal mechanisms involved should be structurally analogous to those of biological evolution. I argue that this is implausible because phenotypical consequences of cultural traits are not causally relevant to their chances of “survival.” (Published Online November 9 2006).

Paperny examines the evolution of architecture in Russia during the Stalinist period. Defining two conflicting trends--Culture One and Culture Two--that have alternately prevailed in Russian culture, the author argues that the shift away from the architectural avant-garde of the 1920s was not entirely the result of Stalin's will. Rather, he demonstrates how the aesthetic choices of Stalin and his architects were conditioned by the prevailing cultural mechanisms of the 1930s and 40s. Combining academic precision with engaging narrative, Paperny leads the (...) reader through the remarkable trajectory of architectural and cultural transformation that marked a pivotal moment of Russia's history. (shrink)

If culture is defined as variation acquired and maintained by social learning, then culture is common in nature. However, cumulative cultural evolution resulting in behaviors that no individual could invent on their own is limited to humans, song birds, and perhaps chimpanzees. Circumstantial evidence suggests that cumulative cultural evolution requires the capacity for observational learning. Here, we analyze two models the evolution of psychological capacities that allow cumulative cultural evolution. Both models suggest that the conditions which allow the evolution of (...) such capacities when rare are much more stringent than the conditions which allow the maintenance of the capacities when common. This result follows from the fact that the assumed benefit of the capacities, cumulative cultural adaptation, cannot occur when the capacities are rare. These results suggest why such capacities may be rare in nature. (shrink)

If culture is defined as variation acquired and maintained by social learning, then culture is common in nature. However, cumulative cultural evolution resulting in behaviors that no individual could invent on their own is limited to humans, song birds, and perhaps chimpanzees. Circumstantial evidence suggests that cumulative cultural evolution requires the capacity for observational learning. Here, we analyze two models the evolution of psychological capacities that allow cumulative cultural evolution. Both models suggest that the conditions which allow the evolution of (...) such capacities when rare are much more stringent than the conditions which allow the maintenance of the capacities when common. This result follows from the fact that the assumed benefit of the capacities, cumulative cultural adaptation, cannot occur when the capacities are rare. These results suggest why such capacities may be rare in nature. (shrink)