28.2.06

Modelling of Stochastic Processes

This is going to be an advanced course in stochastic processes. The main focus is on modelling of complex systems in an multi-agent environment. The course is intended for students of engineering or computer science having already taken a course on elementary probability theory.

Contents:

  1. Basic Definitions
    • Measure Theory
    • Probability Theory
    • Stochastic Process
    • Random Functions
    • Notation
  2. One-Parameter Process
    • One-Parameter Process
    • Operator Representation
  3. Markov Process
    • Markov Property
    • Transition Probability
Lecture Notes (pdf)

12.10.05

Optimal Prediction in Complex Multi-Agent Systems

I am giving a seminar at the Computer Science Department, University of Aberdeen on the Application of Computational Mechanics in Multi-Agent Systems.

more info, slides (2MB pdf)