Simulating Language U00521/P00218 (Honours/MSc course) Lecturer: Simon Kirby

Aims and general description

Although many consider the only interface between computing and linguistics to be speech technology (where linguistic knowledge is used to solve engineering problems), increasingly in recent years computers are being used to explore fundamental problems of theoretical linguistics.

The aim of this course is to give an introduction to some of the techniques of computational modelling and simulation and show how they have been used to shed light on debates in: language acquisition, language change, and language evolution. The focus will be mainly on learning how to assess the literature in these areas, rather than a practical course on simulation techniques. However, simulation packages are available and a small practical project will be an option for part of the course assessment (see below).

Prerequisites

There are no official prerequisites for this course. The course is predominantly theoretical rather than practical, so programming expertise is not a requirement. That said, a practical project is an option for those that are interested.

Syllabus (subject to change - details will appear on WebCT)

1. Introduction: what is a model? and how does it relate to theory? What areas of linguistics could benefit from computational models?
2. Neural networks: a non-mathematical introduction to connectionist approaches to modelling learning.
3. Language acquisition and connectionism: a survey of how neural network models have become central in debates about how children learn linguistic rules.
4. Language change: a brief overview of how simulations are beginning to be used to understand why historical changes seem to have a particular "shape", and where language universals come from.
5. Language evolution: an introduction to how computational techniques such as "genetic algorithms" might be combined with models of acquisition and change to eventually solve the problem of language origins.

Course Structure

The course will be based around readings mostly drawn from the recent research literature. Each week there will be two lectures introducing the reading and placing it in a broad context, and one tutorial with more detailed group discussion of the readings.

Reading

There is no set text for this course. Readings for the majority of the course will be research papers and chapters. These will be available as photocopies in the filing cabinets in the common room, and will be made available a week before the tutorial sessions discussing them. Along with each reading will be a set of questions to be discussed in the tutorial session. More details will be made available on the WebCT page for the course. However, readings will include the following:

• Bechtel, W. and Abrahamsen, A. (1991). Connectionism and the Mind. Chapter 1. "Networks versus Symbol Systems: Two approaches to modeling cognition" pp. 1-20
• Elman, J. et. al. (1996). Rethinking Innateness. Chapter 2. "Why connectionism?" pp. 47-66
• Elman, J. et. al. (1996) pp. 66-106
• Rumelhart & McClelland 1986 “On learning the past tenses of English Verbs”
• Pinker & Prince (1989) "Rules and connections in Human Language"
• Elman, J. (1993). "Learning and development in neural networks: the importance of starting small" Cognition, 48:71-99
• Mitchell, M. (1996) "An introduction to Genetic Algorithms" pp 1-16
• Batali, J. (1994) "Innate biases and critical periods: combining evolution and learning in the acquisition of syntax".
• Christiansen, M. H. and Devlin, J. T. (1997). "Recursive inconsistencies are hard to learn: A connectionist perspective on universal word order correlations".
• Christiansen, M. H. and Ellefson, M. R. (2002). "Linguistic Adaptation Without Linguistic Constraints: The Role of Sequential Learning in Language Evolution".
• Batali, J. (1998) "Computational Simulations of the Emergence of Grammar".
• Kirby, S. & Hurford, J. (2001). "The Emergence of Linguistic Structure: An overview of the Iterated Learning Model." In Angelo Cangelosi and Domenico Parisi, editors, Simulating the Evolution of Language, pages 121--148. London: Springer Verlag.
• Vogt, P. (2003) "Anchoring of semiotic symbols" Robotics and Autonomous Systems. 43(2): 109-120
• Vogt, P. (2000) "Bootstrapping grounded symbols by minimal autonomous robots" Evolution of Communication 4(1): 89-118

Assessment