— A decentralized, adaptive control law is presented to drive a network of mobile robots to a near-optimal sensing configuration. The control law is adaptive in that it integrat...
Mac Schwager, Jean-Jacques E. Slotine, Daniela Rus
This paper discusses how a robot can develop its state vector according to the complexity of the interactions with its environment. A method for controlling the complexity is prop...
In this paper, we first discuss the meaning of physical embodiment and the complexity of the environment in the context of multi-agent learning. We then propose a vision-based rei...
This paper describes an approach to robotic control that is patterned after models of human skill acquisition. The intent is to develop robots capable of learning how to accomplis...
This research concerns the comparison of three different artificial evolution approaches for the design of cooperative behavior in a group of simulated mobile robots. The first an...