The current framework of reinforcement learning is based on maximizing the expected returns based on scalar rewards. But in many real world situations, tradeoffs must be made amon...
Reminder systems support people with impaired prospective memory and/or executive function, by providing them with reminders of their functional daily activities. We integrate tem...
Matthew R. Rudary, Satinder P. Singh, Martha E. Po...
In this paper, we adopt general-sum stochastic games as a framework for multiagent reinforcement learning. Our work extends previous work by Littman on zero-sum stochastic games t...
We consider the problem of finding optimal strategies in infinite extensive form games with incomplete information that are repeatedly played. This problem is still open in lite...
Alessandro Lazaric, Jose Enrique Munoz de Cote, Ni...
Reinforcement learning (RL) is a fundamental process by which organisms learn to achieve a goal from interactions with the environment. Using Artificial Life techniques we derive ...
Yael Niv, Daphna Joel, Isaac Meilijson, Eytan Rupp...