Partially observable markov decision process

Results 251 to 260 of about 35,395 (320)

Quality and Reliability Engineering International, EarlyView.
ABSTRACT This article assesses risk times in mission‐oriented systems with high safety standards. We examine critical times under two safety policies. The first requires that the system's reliability function, known the first failure of the components, must exceed a reliability level throughout the mission.
Antonio Arriaza +2 more
wiley +1 more source

Hippocampus supports multi-task reinforcement learning under partial observability. [PDF]

Nat Commun
Pedamonti D +5 more
europepmc +1 more source

Dynamic Event‐Triggered Robust Model Predictive Control for Quadrotor Trajectory Tracking

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT This paper addresses the trajectory tracking problem for a full‐state quadrotor subject to physical model constraints and unknown external disturbances. A robust tube‐based model predictive control (MPC) approach is successfully applied to the system, which is subject to bounded disturbances and hard constraints.
Ali Can Erüst +2 more
wiley +1 more source

A Cognitive Perspective on Information Frictions in Labor Markets. [PDF]

Entropy (Basel)
Zhang Z, Chen R.
europepmc +1 more source

Perkembangan Perilaku Pembelajaran Peserta Didik dengan Menggunakan Partially Observable Markov Decision Processes

Maxtulus Junedy Nababan
openalex +2 more sources

Why Autonomous Vehicles Are Not Ready Yet: A Multi‐Disciplinary Review of Problems, Attempted Solutions, and Future Directions

Journal of Field Robotics, EarlyView.
ABSTRACT Personal autonomous vehicles can sense their surrounding environment, plan their route, and drive with little or no involvement of human drivers. Despite the latest technological advancements and the hopeful announcements made by leading entrepreneurs, to date no personal vehicle is approved for road circulation in a “fully” or “semi ...
Xingshuai Dong +13 more
wiley +1 more source

Deep Reinforcement Learning Data Collection for Bayesian Inference of Hidden Markov Models. [PDF]

IEEE Trans Artif Intell
Alali M, Imani M.
europepmc +1 more source

Incorporating environmental DNA metabarcoding for improved benthic biodiversity and habitat mapping

Remote Sensing in Ecology and Conservation, EarlyView.
Seafloor imagery is commonly used to collect information about the distribution of benthic organisms in order to generate habitat and biodiversity maps. Recent advances in genomics (e.g., environmental DNA; eDNA) show potential to complement video surveys for habitat mapping, but there have been few examples testing this.
Rylan J. Command +8 more
wiley +1 more source

Human-Risk-Aware Safe Path Planning Based on Reinforcement Learning for Autonomous Mobile Robots. [PDF]

Sensors (Basel)
Long Z, Zhang X, Mi J, Wang J.
europepmc +1 more source

markov and semi-markov decision processes
deep reinforcement learning
dynamic programming

pomdp
markov decision process
fos: computer and information sciences

reinforcement learning
artificial intelligence cs.ai
partially observable markov decision processes