Sensors, Vol. 19, Pages 4055: Decision-Making for the Autonomous Navigation of Maritime Autonomous Surface Ships Based on Scene Division and Deep Reinforcement Learning
Sensors, Vol. 19, Pages 4055: Decision-Making for the Autonomous Navigation of Maritime Autonomous Surface Ships Based on Scene Division and Deep Reinforcement Learning Sensors doi: 10.3390/s19184055 Authors: Zhang Wang Liu Chen This research focuses on the adaptive navigation of maritime autonomous surface ships (MASSs) in an uncertain environment. To achieve intelligent obstacle avoidance of MASSs in a port, an autonomous navigation decision-making model based on hierarchical deep reinforcement learning is proposed. The model is mainly composed of two layers: the scene division layer and an autonomous navigation decision-making layer. The scene division layer mainly quantifies the sub-scenarios according to the International Regulations for Preventing Collisions at Sea (COLREG). This research divides the navigational situation of a ship into entities and attributes based on the ontology model and Protégé language. In the decision-making layer, we designed a deep Q-learning algorithm utilizing the environmental model, ship motion space, reward function, and search strategy to learn the environmental state in a quantized sub-scenario to train the navigation strategy. Finally, two sets of verification experiments of the deep reinforcement learning (DRL) and improved DRL algorithms were designed with Rizhao port as a study case. Moreover, the experimental data were analyzed in terms of the convergence trend, iterative path, and collision ...
Authors: Hanewinkel R PMID: 31623003 [PubMed - in process]
Zum Kommentar von Prof. Reiner Hanewinkel zum Hot Topic-Thema „Raucherentwöhnung: E-Zigarette besser als klassische Nikotinersatzpräparate?“ Pneumologie 2019; 73: 336 – 337. Pneumologie. 2019 Oct;73(10):622 Authors: Pommer P PMID: 31623002 [PubMed - in process]
Authors: Schulz H, Karrasch S, Bölke G, Cyrys J, Hornberg C, Pickford R, Schneider A, Witt C, Hoffmann B PMID: 31623001 [PubMed - in process]
Leserbrief zu Schulz H, Karrasch S, Bölke G et al. Atmen: Luftschadstoffe und Gesundheit – Teil I. Pneumologie 2019; 73: 288 – 305. Pneumologie. 2019 Oct;73(10):617-619 Authors: Schnitzler A PMID: 31623000 [PubMed - in process]
Authors: Schöll N, Rohde GGU Abstract Pneumonia belongs to the most frequent and most deadly infectious diseases worldwide. It represents an increasing problem for the aging population. The incidence and mortality rises with every decade. The clinical presentation of pneumonia differs between elderly and younger patients. Multiple factors including functional status (self-dependency and immobilization), comorbidities, immunosenescence, nutritional status, swallowing disorders have to be accounted for. Pneumonia in the elderly has to be differentiated from nursing home acquired pneumonia. Diagnosis of pneumonia...
Perikardpunktion – Schritt für Schritt. Pneumologie. 2019 Oct;73(10):597-604 Authors: Ferrari MW PMID: 31622998 [PubMed - in process]
Authors: Raspe M, Rolling T, Leisse C, Fischer J, Lehmann C Abstract Infectious Diseases are a cross-sectional area connected to various medical disciplines and offer interested physicians multiple working opportunities. The spectrum of infectious diseases covers both out- and inpatient care as well as basic, clinical and epidemiological research. The need for infectious diseases specialists is increasing, thus career prospects are promising. Working conditions in infectious diseases are comparatively family-friendly. With this article we intend to arouse interest for working in the fascinating fields of infectious...
Authors: Bahmer T, Wälscher J, Fisser C, Kreuter M, Karg O, Böing S, Koczulla R, Raspe M PMID: 31622996 [PubMed - in process]
Lungengesundheit: Beruf als großer Risikofaktor? Pneumologie. 2019 Sep;73(9):e2 Authors: Simon A PMID: 31622984 [PubMed - in process]
20 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: Am J Trop Med Hyg These pubmed results were generated on 2019/10/19PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.