Algorithmic Stackelberg game theory with application in energy pricing

In the past decade there has been a surge of research in algorithmic game theory as the intersection of computer science and economics and algorithmic Stackelberg game theory is a special topic along this direction.
In the existing Stackelberg (also called leader-follower) game theory, there are two fundamental weaknesses: Firstly the perfect information about other players’ behaviour is known; secondly the optimal strategies can be found analytically and accurately. The objectives of the project are to overcome these weaknesses by developing the learning algorithms to learn other players’ behaviour from data and investigating the approximate strategies to play the game effectively and optimistically. As the application, the developed theory and method is to be applied to the energy pricing problem, where the customers are acting as the followers to minimise their energy bills by selecting the best available tariffs and the energy suppliers are acting as the leaders to maximise their profits/market share by offering the right prices to the right customers.

References
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