Reinforcement Learning

Education facts

Code: MT7051

Kursen syftar till att introducera såväl grundläggande som moderna begrepp inom förstärkningsinlärning (reinforcement learning). Detta inkluderar Markovska beslutsprocesser, dynamisk programmering, modellfri prediktion och styrning, temporal-difference learning, funktionsapproximation, policy-gradient och actor-critic-metoder, samt moderna tillämpningar av förstärkningsinlärning.

Entry requirements

For admission to the course, knowledge equivalent to Stochastic Processes and Simulation I, 7.5 ECTS credits (MT4002), Probability Theory II, 7.5 ECTS credits (MT5018) and either Programming Techniques for Mathematicians, 7.5 ECTS credits (DA2004) or Statistical Data Processing, 7.5 ECTS credits (MT4007) is required. Also required is Swedish upper secondary school course English 6 or equivalent.

Education offerings

Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.

• Reinforcement Learning

  Stockholm University

  Stockholm

  Start date: 3 November 2026

  End date: 17 January 2027

  Pace of study: 50 %