Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
Carlos Diuk, Alexander L. Strehl, Michael L. Littm...
This paper presents the design and implementation of the Distributed Autonomous Replication Management (DARM) framework built on top of the Spread group communication system. The ...
Biological systems are traditionally studied by focusing on a specific subsystem, building an intuitive model for it, and refining the model using results from carefully designed ...
Irit Gat-Viks, Amos Tanay, Daniela Raijman, Ron Sh...
— Fault diagnosis of coupled mobile robots requires a large number of measurements to be communicated either between the robots or from the robots to a central diagnoser. As comp...
Matthew J. Daigle, Xenofon D. Koutsoukos, Gautam B...
We propose an open and extensible agent-based formal framework for modeling and simulating supply chains. Since structures and behaviors of supply chains can be very different bas...