Note from June 29, 2020
Although we do not yet know how long the social distancing related to the Covid-19 pandemic will last, and regardless of the changes that had to be made in the evaluation of the June 2020 session in relation to what is provided for in this learning unit description, new learnig unit evaluation methods may still be adopted by the teachers; details of these methods have been - or will be - communicated to the students by the teachers, as soon as possible.
Although we do not yet know how long the social distancing related to the Covid-19 pandemic will last, and regardless of the changes that had to be made in the evaluation of the June 2020 session in relation to what is provided for in this learning unit description, new learnig unit evaluation methods may still be adopted by the teachers; details of these methods have been - or will be - communicated to the students by the teachers, as soon as possible.
4 credits
12.0 h + 36.0 h
Q1
Teacher(s)
Wesselingh Renate;
Language
French
Prerequisites
Ecology, evolution, statistics. Some basic knowledge of the R language is useful, but not strictly necessary
Main themes
Analytical and simulation models, game theory, Evolutionarily Stable Strategies, population- and individual-based models, spatial models.
Aims
At the end of this learning unit, the student is able to : | |
| 1 | This course will teach the different categories of ecological and evolutionary models, how to formalize ecological and evolutionary processes and turn them into analytical and simulation models using R, and how to use the results of such models. |
The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
Bibliography
Railsback, S.F. & V. Grimm (2019) Agent-based and individual-based modelling, 2nd edition. Princeton University Press, Princeton, NJ, USA.
Faculty or entity
BIOL
