Adaptive learning/ reinforcement learning, has been covered under Dynamic Programming for decades. Dynamic programming is designed on the divide-and-conquer basis which fits well into the computing concepts for MSc Optimisation and Analytics and MSc Data Science. The stochastic version of DP links closely with the stochastic process, with the similar idea of describing the problem status by stages, states and transition matrices, but allowing decisions in the whole process. So this module fits naturally well into the current course structure, whereas compensates what we are offering by linking several topics (maths and computing, deterministic and stochastic) together
- Module Supervisor: Felipe Maldonado