This paper takes the first steps towards designing incentive compatible mechanisms for hierarchical decision making problems involving selfish agents. We call these Stackelberg p...
One of the most challenging problems in high-level synthesis is how to quickly explore a wide range of design options to achieve high-quality designs. This paper presents an Integ...
Qingfeng Zhuge, Zili Shao, Bin Xiao, Edwin Hsing-M...
Abstract. Most existing evolutionary approaches to multiobjective optimization aim at finding an appropriate set of compromise solutions, ideally a subset of the Pareto-optimal se...
Johannes Bader, Dimo Brockhoff, Samuel Welten, Eck...
The global scenario put together by communication networks determines new opportunities towards the realization of Internetbased distributed services in many complex and composite...
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...