Game-Theoretic Approaches to Environmental Risk
This PhD research will explore:
- How can mathematical modelling and game-theory help us to understand the economic, behavioural and psychological factors and incentives affecting the incentives for governments and nations to form international environmental agreements (IEAs) in the first place, and to adhere to these agreements over the long term, when there are individual incentives to renege and free-ride?
- What do the models tell us about the large number of existing IEA failures, and what implications do they provide for the future?
- How can these models help us to develop stronger and more stable IEAs, with greater hope for the planet’s climate and survival?
The research will consider this at both the governmental/societal level, and the individual firm/consumer level.
Develop a model which integrates game theory with collective intelligence-based approaches integrated with machine learning. The vision is to develop this model to the implementation stage. This will enable a deeper understanding of how governmental bodies and international bodies are influenced by Influencers and their citizens to adhere to IEA agreements. The research explores a mathematical model, with psychological metrics in mind.
The aim of the game-theoretic model is to analyse interactions between international governments, political bodies, and each nation's internal pressures from its own citizens and super-influencers. The model will analyse the conditions for large, effective and stable IEAs to form, and for international governments to adhere to strong environmental targets in equilibrium, and will consider the conditions under which such agreements would break down. The objective is that this analysis will provide clear policy implications for future successful IEAs in the real-world, which will be of immense benefit to the future of the planet.
Skills required
The candidate should have a minimum of BSc (2:1) degree, or equivalent, in computation or applied mathematics. He/she will have an understanding of cooperative game theory and a understanding of machine learning techniques behaviour modelling. It would also be advantageous if the candidate has previous knowledge of computational social behaviour models. The candidate should also be familiar with Java and Python programming languages. The successful candidate will have an innovative, flexible ethos and be able to implement new ideas constructively to emerging concepts. Full-time or part-time applicants are welcome.
Background reading
The Manufacturing Sector's Environmental Motives: A Game-Theoretic Analysis on JSTOR
Other relevant publications identified by the project team include:
Contact
Dr Dhouha Kbaier and Dr Ian Kenny.
We have also collaborators from the University of Bath who will be external supervisors as well.
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