We propose an automata-theoretic approach for reinforcement learning (RL...
We study distributed planning for multi-robot systems to provide optimal...
In many applications, the integrals and derivatives of signals carry val...
We present a novel reinforcement learning algorithm for finding optimal
...
We investigate a multi-agent planning problem, where each agent aims to
...
Signal temporal logic (STL) is an expressive language to specify time-bo...
We address the problem of achieving persistent surveillance over an
envi...
We investigate the distributed planning of robot trajectories for optima...