Here are the slides from Lectures

8_Continuous Time Dynamic Programming

Please read Section 2.1 of the notes

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# Category: Uncategorized

## Continuous Time Dynamic Programming

## LQR and Kalman Filter

## ODE method for Stochastic Approximation

## Optimal Stopping

## Algorithms for MDPs

## Infinite Time Horizon MDP

## Markov Decision Processes

## Markov Chains

## Dynamic Programming

## Stochastic Control 2020

Here are the slides from Lectures

8_Continuous Time Dynamic Programming

Please read Section 2.1 of the notes

Here are the slides from Lectures

Please read these notes [which will be later added to the main set of notes]:

We consider the Robbins-Monro update

and argue that this can be approximated by the o.d.e.:

Here are the slides from Lectures

Please read Section 1.6 from the notes:

Please attempt Ex53, Ex54, Ex56, Ex57.

Here are the slides from Lectures

Please read Section 1.5 from the notes:

Please attempt Ex39, 40 & 41 [if you can code], 42 and 43.

Here are the slides from Lectures

Please read Section 1.4 from the notes:

Please attempt Ex35, Ex36, Ex37.

Here are the slides from Lectures

3_Markov Decision Processes [pdf]

Please read Section 1.3 from the notes:

Please attempt exercises Ex22, Ex23, Ex24, Ex25.

Here are the slides from Lectures

Please read Section 1.2 from the notes:

Slides from Lectures are here:

Please read Section 1.1 of the notes:

Stochastic Control Notes [pdf]

Please attempt exercises **Ex3, Ex5 **and** Ex6** from the notes.

Another year of MATH69122! — aka Stochastic Control.

This year, I will try to keep updating PDFs with slides and notes for each lecture. I’ll keep notes for the course in the “PDF” tab above. These are also here:

Here is a rough plan for each week of lectures: