Unlike traditional reinforcement learning (RL), market-based RL is in principle applicable to worlds described by partially observable Markov Decision Processes (POMDPs), where an ...
We consider the problem of incorporating end-user advice into reinforcement learning (RL). In our setting, the learner alternates between practicing, where learning is based on ac...
Kshitij Judah, Saikat Roy, Alan Fern, Thomas G. Di...
The potentially catastrophic impact of a bioterrorist attack makes developing effective detection methods essential for public health. In the case of anthrax attack, a delay of ho...
Proactive assessment of computer-network vulnerability to unknown future attacks is an important but unsolved computer security problem where AI techniques have significant impact...
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...