Indicator-based algorithms have become a very popular approach to solve multi-objective optimization problems. In this paper, we contribute to the theoretical understanding of alg...
Policy teaching considers a Markov Decision Process setting in which an interested party aims to influence an agent’s decisions by providing limited incentives. In this paper, ...
One of the most controversial yet enduring hypotheses about what genetic algorithms (GAs) are good for concerns the idea that GAs process building-blocks. More specifically, it ha...
The main aim of randomized search heuristics is to produce good approximations of optimal solutions within a small amount of time. In contrast to numerous experimental results, th...
Tobias Friedrich, Nils Hebbinghaus, Frank Neumann,...
We address the problem of lowering the buyer’s expected payments in shortest path auctions, where the buyer’s goal is to purchase a path in a graph in which edges are owned by...