—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
Zhengqiao Ji, Q. M. Jonathan Wu, Maher A. Sid-Ahme...
Aggressive technology scaling into the nanometer regime has led to a host of reliability challenges in the last several years. Unlike onchip caches, which can be efficiently prot...
Amin Ansari, Shuguang Feng, Shantanu Gupta, Scott ...
Social insect societies and more specifically ant colonies, are distributed systems that, in spite of the simplicity of their individuals, present a highly structured social organi...
The need for rapid and cost-effective development Intelligent Tutoring Systems with flexible pedagogical approaches has led to a demand for authoring tools. The authoring systems ...
Constructing models of mobile agents can be difficult without domain-specific knowledge. Parametric models flexible enough to capture all mobility patterns that an expert believes...
Joshua Mason Joseph, Finale Doshi-Velez, Nicholas ...