We consider a problem domain where coalitions of agents are formed in order to execute tasks. Each task is assigned at most one coalition of agents, and the coalition can be reorg...
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, ...
Information systems often require combining datasets available in different formats, and geographical information systems are no exception. While semantic technologies have been u...
In this paper, we give the rst constant-factor approximationalgorithmfor the rooted Orienteering problem, as well as a new problem that we call the Discounted-Reward TSP, motivate...
Avrim Blum, Shuchi Chawla, David R. Karger, Terran...
As learning agents move from research labs to the real world, it is increasingly important that human users, including those without programming skills, be able to teach agents de...