Multiagent systems are often characterized by complex, and sometimes unpredictable interactions amongst their autonomous components. While these systems can provide robust and sca...
Wilbur Peng, William Krueger, Alexander Grushin, P...
We investigate and model the dynamics of two-dimensional stochastic self-assembly of intelligent micro-systems with minimal requirements in terms of sensing, actuation, and contro...
We introduce a study of position auctions, with an explicit modeling of user navigation through ads. We refer to our model as the PPA model, since it is most applicable in the con...
In several agent-oriented scenarios in the real world, an autonomous agent that is situated in an unknown environment must learn through a process of trial and error to take actio...
Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...