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Expert profile — Profil d'expert

hhoos's picture
Holger H. Hoos
Primary area of expertise
Stochastic search
Secondary area of expertise
empirical algorithmics
Other areas of expertise
bioinformatics, computer music,
Short biographical note
Hard combinatorial problems occur in many areas of computer science and its applications, such as Artificial Intelligence, Bioinformatics, and Electronic Commerce. Although theoretical complexity results suggest that most of these problems are exponentially hard in the worst-case, this does not always mean that they cannot be solved reasonably effectively in practice. One of my primary research interests is to study hard combinatorial problems, and to explore algorithmic ways of solving them as efficiently as possible in practical applications.

In this context, I am particularly interested in stochastic search algorithms that combine goal-directed, greedy search with randomised decisions. This group of algorithms includes general algorithmic techniques such as simulated annealing, evolutionary algorithms, ant-colony optimisation, or stochastic hill-climbing, as well as problem-specific algorithms. I have been working on various types of stochastic local search algorithms, investigated and modelled their behaviour, and developed new, improved algorithms for various applications, such as the satisfiability in propositional logic (SAT), the travelling salesperson problem (TSP), or winner-determination in combinatorial auctions. Currently, I am particularly interested in studying and developing stochastic search techniques for problems in bioinformatics, biocomputing, artificial intelligence, and electronic commerce.


2013 AI Doctoral and MSC thesis awards

 AI 2018
31st Canadian Conference on Artificial Intelligence


8-11 May 2018, Toronto, Ontario



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