Although several researchers have integrated methods for reinforcement learning (RL) with case-based reasoning (CBR) to model continuous action spaces, existing integrations typic...
: The standard continuous time state space model with stochastic disturbances the mathematical abstraction of continuous time white noise. To work with well defined, discrete time ...
: In this paper, we present a sampling-based verification algorithm for continuous dynamic systems with uncertainty due to adversaries, unmodeled disturbance inputs, unknown parame...
This paper is concerned with developing an information-theoretic framework to aggregate the state space of a Hidden Markov Model (HMM) on discrete state and observation spaces. The...
This work deals with trajectory optimization for a network of robotic sensors sampling a spatio-temporal random field. We examine the problem of minimizing over the space of networ...