Abstract. In concrete environments, where uncertainty and dynamism are pervasive and time and resources are limited, reasoning and decision-making processes raise important problem...
A major challenge for traditional approaches to multiagent learning is to train teams that easily scale to include additional agents. The problem is that such approaches typically...
David B. D'Ambrosio, Joel Lehman, Sebastian Risi, ...
In this paper, we investigate the coverage problem in wireless sensor networks using a game theory method. We assume that nodes are randomly scattered in a sensor field and the goa...
Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are evolving as a popular approach for modeling multiagent systems, and many different algorithms ha...
This paper addresses the problem of object detection and recognition in complex scenes, where objects are partially occluded. The approach presented herein is based on the hypothe...