We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
Background: Predicting a protein’s structural class from its amino acid sequence is a fundamental problem in computational biology. Much recent work has focused on developing ne...
Iain Melvin, Eugene Ie, Rui Kuang, Jason Weston, W...
Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...
Abstract. We present the discrete beeping communication model, which assumes nodes have minimal knowledge about their environment and severely limited communication capabilities. S...
In this paper, we describe ChucK – a programming language and programming model for writing precisely timed, concurrent audio synthesis and multimedia programs. Precise concurre...