Yes. There is no programming required for this course and none of it is assessed. The textbook includes optional Python for those who want to explore the ideas computationally, but you do not need to write or run any code to do well.
No. There is no programming required for this module: it is not assessed and you do not need to write or run any code to do well. The Python in the textbook is entirely optional. It is there so you can explore the ideas computationally and check your working if you would like to, but you are welcome to ignore it.
If you do want to try it and are not familiar with Python, these chapters of Python For Mathematics on installing and using Python and installing and using other libraries are a good place to start.
You may, but be deliberate about how. The examination is closed-book with no generative AI, so the only thing that matters on the day is what you can do yourself.
In a field experiment with nearly a thousand mathematics students, those with unrestricted access to GPT-4 did much better on practice problems, but once access was removed they did worse on the exam than students who had never used it. A version of the tutor constrained to give hints rather than answers removed most of that harm.
So use an LLM in ways that keep you doing the thinking: ask it to quiz you on the definitions, ask for a hint rather than a solution, or show it an attempt you have already written and ask it to find the error. Do not ask it to answer an example question before you have attempted that question in full yourself. Otherwise you are practising for an examination that the AI sits, and not the one that you will.
The aim of the course is that you can do game theory: state and prove the results, compute the equilibria and interpret what they mean. A closed-book examination is the most direct and fair way to assess that.
The research is consistent about what happens when you hand your thinking over. A study in PNAS found that students with access to GPT-4 improved on practice problems but did worse than their peers once access was removed. A study of 666 participants linked heavier AI use to weaker critical thinking through cognitive offloading, and a brain-imaging study at MIT found that essay writers using an LLM had the poorest recall of their own work. None of this is new: Kirschner, Sweller and Clark argued two decades ago that learning is a change in long-term memory, and that teaching fails when it leaves the learner consulting a source instead of building knowledge of their own.
You will certainly use AI tools in your working life, but they are most useful to people who understand the material well enough to direct them and to catch their mistakes. That understanding is what this course, and its examination, are for.
A bribentive is a word we use in class for the small rewards handed out during some activities. It is a blend of bribe and incentive: the reward is usually just a sweet or a chocolate bar, so it is not really a good incentive, more a small bribe for engagement. The games still work without it, but it adds a bit of fun to the competition.