Teaching

This is a brief overview of various teaching activities.

Interested students, please see projects below.

Courses

Currently, I have the following teaching duties:

I am module coordinator for COMP219: Articicial Intelligence. [COMP219 website]
I am module coordinator for COMP281: Principles of C and Memory Management.

In the past, I have given a number of 'courses' at Maastricht Univerrsity:

Introduction to Programming.
University College Maastricht, Maastricht University, 2013.
This course gave a first introduction to programming in Java by building in the Processing framework.
Computer Science 2.
Dept. of Knowledge Engineering, Maastricht University, 2013.
This course focused on more advanced concepts in programming Java.
Scientific Computing
Maastricht Science Program of the Maastricht Science College, 2012, 2013.
- Scientific Computing 2013 was slightly less technical.
- Scientific Computing 2012 went into more technical detail on certain topics.

I have taught:

Decision making under uncertainty. Jointly with Matthijs Spaan at EASSS'12 at Valencia and EASSS'13 at KCL.
Cooperative Decision Making in Sequential Multiagent Settings at AAMAS 13. Jointly with Christopher Amato, Prashant Doshi, Zinovi Rabinovich, Matthijs Spaan, & Stefan Witwicki.
Self-Interested Decision Making in Sequential Multiagent Settings at AAMAS 13. Jointly with Christopher Amato, Prashant Doshi, Zinovi Rabinovich, Matthijs Spaan, & Stefan Witwicki.

Advanced Topics in Autonomous Agents (UvA). Decentralized POMDPs. 2013, 2014, 2015. download (pdf).
6.882: Planning and Decision Making (MIT). Decision Making for Cooperative Agents: Multiagent MDPs, Decentralized MDPs & POMDPs November 23, 2010. download (pdf).
Multiagent sytems and distributed AI (MASDAI), UvA, 2008 and 2009. download (pdf).
Decision making in intelligent systems (DMIS), UvA, April 14th 2008, May 4th 2009. download (pdf).

I am involved in the supervision of various students at UvA and UoL.

I am very interested in supervising students in the following direction(s):

Decision Making for Traffic (Light) Control

The optimization of traffic and traffic lights is a difficult problem with a huge potential for real-world impact. If you are interested in doing something that relates to traffic, I would be happy to talk to you.
Formal Decision Making with Practical Communication

Formal models of multiagent decision making provide a basis for finding optimal policies. However, current formal models make impractical assumptions with respect to communication. For instance they assume full communication of all private sensor data or the existence of abstract communication utterances of which the optimal meaning must be found during planning. However, it is often relatively simple for a human designer to anticipate in what situations communication can be helpful. Therefore, in this project we will develop formal models that incorporate communication with fixed semantics. Such models will allow the agents to better coordinate without sharing all their private information or further complicating the planning process.