Abstract Partially observable Markov decision processes (POMDPs) are a principled mathematical framework for planning under uncertainty, a crucial capability for reliable operation...
Hanna Kurniawati, Yanzhu Du, David Hsu, Wee Sun Le...
Abstract. Robots coordinate among themselves to select one of them to respond to an event reported to one of robots. The goal is to minimize the communication cost of selecting bes...
A function of a protein is dependent on its structure; therefore, predicting a protein structure from an amino acid sequence is an active area of research. Optimally predicting a ...
This paper describes a way to manage the modeling and analysis of Scheduled Maintenance Systems (SMS) within an analytically tractable context. We chose a significant case study h...
This paper introduces a Bayesian algorithm for constructing predictive models from data that are optimized to predict a target variable well for a particular instance. This algori...