Research areas and current projects
Our research is concerned with modeling complex (and often stochastic) search and optimization problems and solving them through computational heuristics. A special emphasis is given to distributed problems arising in social multi-agent systems, which cannot be optimized by pure economic price coordination. Imposing a solution by a central planner will often be rejected by the involved autonomous agents. Therefore, we need to design distributed mechanisms that provide incentives to participate to the individual agents without deviating too much from a pareto-efficient solution. We apply these methods to various domains, leading the following complementary areas of research.
Further advancements of nature-inspired processes (Simulated Annealing, Genetic Algorithms, Connectionist Models) for stochastic and dynamic problems as well as suitable parallelization of the methods for the application in distributed systems (e.g. Peer-to-Peer-/Multi-Agent Systems).