Language Evolution and Computation Bibliography

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Stephan Lewandowsky
2009
Cognitive Science 33(6):969--998, 2009
Abstract Determining the knowledge that guides human judgments is fundamental to understanding how people reason, make decisions, and form predictions. We use an experimental procedure called ''iterated learning,''in which the responses that people give ...
2008
Philosophical Transactions of the Royal Society B: Biological Sciences 363(1509):3503-3514, 2008
The question of how much the outcomes of cultural evolution are shaped by the cognitive capacities of human learners has been explored in several disciplines, including psychology, anthropology and linguistics. We address this question through a detailed investigation of ...MORE ⇓
The question of how much the outcomes of cultural evolution are shaped by the cognitive capacities of human learners has been explored in several disciplines, including psychology, anthropology and linguistics. We address this question through a detailed investigation of transmission chains, in which each person passes information to another along a chain. We review mathematical and empirical evidence that shows that under general conditions, and across experimental paradigms, the information passed along transmission chains will be affected by the inductive biases of the people involved-the constraints on learning and memory, which influence conclusions from limited data. The mathematical analysis considers the case where each person is a rational Bayesian agent. The empirical work consists of behavioural experiments in which human participants are shown to operate in the manner predicted by the Bayesian framework. Specifically, in situations in which each person's response is used to determine the data seen by the next person, people converge on concepts consistent with their inductive biases irrespective of the information seen by the first member of the chain. We then relate the Bayesian analysis of transmission chains to models of biological evolution, clarifying how chains of individuals correspond to population-level models and how selective forces can be incorporated into our models. Taken together, these results indicate how laboratory studies of transmission chains can provide information about the dynamics of cultural evolution and illustrate that inductive biases can have a significant impact on these dynamics.
Philosophical Transactions of the Royal Society B: Biological Sciences 363(1509):3469-3476, 2008
The articles in this theme issue seek to understand the evolutionary bases of social learning and the consequences of cultural transmission for the evolution of human behaviour. In this introductory article, we provide a summary of these articles (seven articles on the ...MORE ⇓
The articles in this theme issue seek to understand the evolutionary bases of social learning and the consequences of cultural transmission for the evolution of human behaviour. In this introductory article, we provide a summary of these articles (seven articles on the experimental exploration of cultural transmission and three articles on the role of gene-culture coevolution in shaping human behaviour) and a personal view of some promising lines of development suggested by the work summarized here.
2007
Iterated learning: Intergenerational knowledge transmission reveals inductive biasesPDF
Psychonomic Bulletin and Review 14(2):288-294, 2007
Cultural transmission of information plays a central role in shaping human knowledge. Some of the most complex knowledge that people acquire, such as languages or cultural norms, can only be learned from other people, who themselves learned from previous generations. The ...MORE ⇓
Cultural transmission of information plays a central role in shaping human knowledge. Some of the most complex knowledge that people acquire, such as languages or cultural norms, can only be learned from other people, who themselves learned from previous generations. The prevalence of this process of iterated learning as a mode of cultural transmission raises the question of how it affects the information being transmitted. Analyses of iterated learning under the assumption that the learners are Bayesian agents predict that this process should converge to an equilibrium that reflects the inductive biases of the learners. An experiment in iterated function learning with human participants confirms this prediction, providing insight into the consequences of intergenerational knowledge transmission and a method for discovering the inductive biases that guide human inferences.