Abstract. As the scale and scope of multi-agent systems grow, it becomes increasingly important to design and manage the manner in which the participants interact. The potential fo...
An original Reinforcement Learning (RL) methodology is proposed for the design of multi-agent systems. In the realistic setting of situated agents with local perception, the task o...
We study the complexity of influencing elections through bribery: How computationally complex is it for an external actor to determine whether by a certain amount of bribing voter...
Piotr Faliszewski, Edith Hemaspaandra, Lane A. Hem...
Algorithmic mechanism design considers distributed settings where the participants, termed agents, cannot be assumed to follow the protocol but rather their own interests. The pro...
We examine whether and how the Multiagent Plan Coordination Problem, the problem of resolving interactions between the plans of multiple agents, can be cast as a Distributed Const...