Partially Observable Markov Decision Processes (POMDPs) provide a rich framework for sequential decision-making under uncertainty in stochastic domains. However, solving a POMDP i...
Abstract— We propose a planning algorithm that allows usersupplied domain knowledge to be exploited in the synthesis of information feedback policies for systems modeled as parti...
Salvatore Candido, James C. Davidson, Seth Hutchin...
We present the Piecewise Linear Approximation Model of Ion Channel contribution (PLAMIC) to cardiac excitation. We use the PLAMIC model to conduct formal analysis of cardiac arrhyt...
Pei Ye, Radu Grosu, Scott A. Smolka, Emilia Entche...
The goal of this project is to develop an agent capable of learning and behaving autonomously and making decisions quickly in a dynamic environment. The agent’s environment is a...
The goal of testing is to discriminate between multiple hypotheses about a system--for example, different fault diagnoses--by applying input patterns and verifying or falsifying t...