AISB convention 2017

  In the run up to AISB2017 convention, I've asked Joanna Bryson, from the organising team, to answer few questions about the convention and what comes with it. Mohammad Majid al-Rifaie ( Tu...


Harold Cohen

Harold Cohen, tireless computer art pioneer dies at 87   Harold Cohen at the Tate (1983) Aaron image in background   Harold Cohen died at 87 in his studio on 27th April 2016 in Encintias California, USA.The first time I hear...


Dancing with Pixies?...

At TEDx Tottenham, London Mark Bishop (the former chair of the Society) demonstrates that if the ongoing EU flagship science project - the 1.6 billion dollar "Human Brain Project” - ultimately succeeds in understanding all as...


Computerised Minds. ...

A video sponsored by the society discusses Searle's Chinese Room Argument (CRA) and the heated debates surrounding it. In this video, which is accessible to the general public and those with interest in AI, Olly's Philosophy Tube ...


Connection Science

All individual members of The Society for the Study of Artificial Intelligence and Simulation of Behaviour have a personal subscription to the Taylor Francis journal Connection Science as part of their membership. How to Acce...



AISB opportunities Bulletin Item

Open PhD position at KaHO St Lieven, Ghent (Belgium)

Research Group IT, KaHo Sint-Lieven, Association K.U.Leuven, Ghent
(Belgium) has an open position for a PhD student for a 4 years project
Intelligent Hyper-heuristics; a tool for solving generic optimisation

The topic of this research aims at a cross-fertilisation of two
interesting research fields, i.e. Meta-heuristics optimisation and
Reinforcement Learning. Meta-heuristics are known to offer very
effective solutions to many of today's challenging combinatorial
optimisation problems appearing in various industrial, economical, and
scientific domains such as bio-informatics, logistics, engineering,
business, etc. Problems like scheduling, timetabling, vehicle routing, 
resource allocation are successfully tackled with meta-heuristic
approaches such as simulated annealing, tabu search, ant colony
optimisation, scatter search, iterated local search, 
etc. Reinforcement learning on the other hand is the problem faced by an
agent that learns behaviour through trial-and-error interactions with a
dynamic environment.  On each step of interaction the agent receives a
reinforcement and some indication of the current state of the 
environment, and chooses an action. The agent's job is to find a policy
mapping states to actions, that maximises some long-run measure of
reinforcement. In this project the aim is to combine meta-heuristics and
reinforcement learning to develop more general hyper-heuristic solutions
for all kinds of optimisation problems. 

Candidates applying for this position will start a PhD programme in
Computer Science at the Katholieke Universiteit Leuven The research project will start at October 1st
2008 at the latest.

Candidates have a master degree in Computer Science or Informatics
preferentially with expertise 
in the fields of Artificial Intelligence, Operational Research and/or
have experienced programming skills. 

Interested applicants should submit as soon as possible: 
(i) Curriculum vitae, 
(ii) List of university exam results, 
(iii) List of references and their email addresses. 

Submit your application as plain text file (or pdf) by email to

Dr. ir. Greet Vanden Berghe
Dr. Katja Verbeeck

KaHo Sint-Lieven
Gebr. Desmetstraat 1
B-9000 Gent
Tel +32 9 2658610
Fax +32 9 2256269