Course Description
The course provides an overview of a selection of mathematical and computational
models of language evolution. It covers agent-based models, evolutionary game theory
and iterated learning models. Our goal is to understand the merits and shortcomings
of each kind of modeling approach as a tool to study language evolution.
Schedule
| Session | Date | Topic | Background reading |
| 1 | 25.10.2018 | Introduction and Overview | Smith (2014) |
| - | 01.11.2018 | no class | |
| 2 | 08.11.2018 | Agent-based models | Loreto et al. (2010) |
| 3 | 15.11.2018 | Evolutionary game theory & signaling | Franke & Wagner (2013) |
| 4 | 22.11.2018 | Evolutionary stability & meaning | Chapter 3 of Skyrms (2010) |
| 5 | 29.11.2018 | Replicator dynamic | |
| 6 | 06.12.2018 | Iterated learning | Kirby, Griffith, Smith (2014) |
| 7 | 13.12.2018 | Recap, midterm prep | [practice questions] |
| 8 | 20.12.2018 | Midterm exam | -- |
| Christmas break | |||
| 9 | 10.01.2019 | cancelled | |
| 10 | 17.01.2018 | Co-Evolution of semantic meaning & pragmatic use | Brochhagen, Franke & van Rooij (2018) |
| 11 | 24.01.2019 | Language evolution in the lab | Scott-Phillips & Kirby (2010) |
| 12 | 31.01.2019 | guest lecture by Vinicius Macuch Silva | |
| 13 | 07.02.2019 | cognitive biases, cultural and biological evolution ::: final discussion | Thompson, Kirby & Smith (2016) |
Reading