Learning for multi-agent systems
    Data mining

The Artificial Intelligence lab

At a glance:
  • Faculty: Science
  • 40 researchers
  • Main areas of expertise:
    • Machine Learning
    • Recommender Systems,
    • Reinforcement Learning,
    • Multi-Agent Systems,
    • Deep Learning,
    • Genetic Algorithms,
    • Neural Networks,
    • Support Vector machines,
    • Graphical models including Bayesion Networks,
    • Bioinformatics.

Machine Learning and Learning in single and multi agent systems.

A strong tradition in Artificial Intelligence

The Artificial Intelligence Laboratory at the Vrije Universiteit Brussel, or the VUB AI Lab, was founded in 1983 br Prof. Luc Steels and has conducted pioneering research ever since.

The research at the AI Lab is organized around two major research tracks: Machine Learning techniques for data mining application & Evolution, and Learning in Single as well as Multi-Agent Systems.

They apply machine learning techniques in a wide range of application domains, including telecom, medicine, supply chain management, smart grids, energy management, etc.


Learning in Multi-Agent Systems

Telecommunications, economics, mobile robots, smart grids, traffic simulation, ... are all examples of systems in which decentralisation of data and/or distribution of control is either required or inherently present. Moreover, in many such systems an exact model of the problem is not available, so exact planning methods are not applicable. The use of multiple interacting learning agents is a necessity to solve these problems. In such systems, where multiple agents are acting, the standard independent learning approaches don't scale up, so alternative approaches are required. Multi-agent Reinforcement learning is such a technique which is capable of dealing with multiple autonomous agents acting and learning in the same environment.

The AI lab has experience in a wide range of learning techniques such as:

  • Reinforcement Learning,
  • Genetic Algorithms,
  • Neural Networks,
  • Support Vector Machines,
  • Graphical models including Bayesian Networks.

Machine learning for Data mining

Machine Learning is at the very heart of Big Data. Machine Learning, related to data science, data mining, or predictive analytics, is one of the most important research topics at the VUB Artificial Intelligence Lab (AI Lab) since its foundation in 1983. This research concerns both the Machine Learning techniques and their application to several domains such as credit card fraud detection, health informatics, bioinformatics, music classification, and the smart grid. Over the years the AI Lab has gathered a lot of experience in both

  1. the development and application of Machine Learning techniques
  2. the handling of: how to store, retrieve and merge large amounts of data while taking interoperability, privacy, security and scalability into account.

These two aspects are at the core of Big Data.

The lab has a vast experience with different Machine Learning techniques for Data Mining and Modeling.

Some of our projects...

In het kort:

De vakgroep Artificiële Intelligentie (AI) voert onderzoek naar het gebruik van AI in toepassingen als machine learning, zelflerende systemen, recommender systemen, en nog veel meer. 

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