Why choose this project topic?
A focused study of finite minimax games gives you a specific question in game theory. It compares algebraic and optimisation representations of mixed-strategy equilibria in small games. The bounded comparison creates room to explain how your evidence supports an interpretation and where the method has limits.
How do primal and dual linear programmes recover optimal mixed strategies and the value of selected zero-sum games?
Agree the apparatus or dataset, comparison range and feasible measurement schedule for finite minimax games with your supervisor.
Proposed project objectives
- 01Define the materials, variables and comparison conditions for finite minimax games.
- 02State payoff orientation and probability constraints explicitly.
- 03Evaluate the measurements or model outputs in relation to this question: How do primal and dual linear programmes recover optimal mixed strategies and the value of selected zero-sum games?
A suggested research approach
State payoff orientation and probability constraints explicitly. Solve small examples, verify best-response inequalities and explain the minimax relationship, including degenerate cases with multiple optimal strategies. Agree the available resources and record uncertainty, deviations from the protocol and any observations that challenge the initial interpretation.
What you will need
- Finite payoff matrices with stated conventions
- Minimax and linear-programming references
- Exact or certified optimisation calculations
Keep your project scope clear
A zero-sum model is a mathematical assumption and does not describe every strategic interaction or real negotiation.
Mathematics project chapter outline
Use this outline as a starting point. You can edit the chapter titles to match your department’s format during setup.
- Chapter 1Introduction
- Chapter 2Literature Review
- Chapter 3Theory and Methodology
- Chapter 4Results and Applications
- Chapter 5Summary, Conclusion and Recommendations
Turn this topic into your own final year project.
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