Transfer learning is the ability of an agent to apply knowledge learned in previous tasks to new problems or domains. We approach this problem by focusing on model formulation, i....
We study how decentralized agents can develop a shared vocabulary without global coordination. Answering this question can help us understand the emergence of many communication s...
In many sensing applications we must continuously gather information to provide a good estimate of the state of the environment at every point in time. A robot may tour an environ...
Alexandra Meliou, Andreas Krause, Carlos Guestrin,...
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
An ant deposits pheromone along the path that it travels and is more likely to choose a path with a higher concentration of pheromone. The sensing and dropping of pheromone makes ...
Sameena Shah, Ravi Kothari, Jayadeva, Suresh Chand...