Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Yaowen Zhang"'
Publikováno v:
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783030675363
In this paper, we consider a scenario where a team of predator robots collaboratively survey an area for preventing the invasion from opponent robots. In this scenario, the predator robots can share the sensing information of the prey robots through
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f8cafe3c6932c70af04497950f8e2173
https://doi.org/10.1007/978-3-030-67537-0_36
https://doi.org/10.1007/978-3-030-67537-0_36
Publikováno v:
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783030675363
The practical application of reinforcement learning agents is often bottlenecked by the duration of training time. To accelerate training, practitioners often turn to distributed reinforcement learning architectures to parallelize and accelerate the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e9d16c51347d083fc936e715b254015d
https://doi.org/10.1007/978-3-030-67537-0_21
https://doi.org/10.1007/978-3-030-67537-0_21
Publikováno v:
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783030926373
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::901ff84c369ffadf7d95ef738b9e5060
https://doi.org/10.1007/978-3-030-92638-0_22
https://doi.org/10.1007/978-3-030-92638-0_22
Publikováno v:
Advances in Knowledge Discovery and Data Mining ISBN: 9783319180311
PAKDD (2)
PAKDD (2)
Most studies about sentiment analysis on microblogging usually focus on the features mining from the text. This paper presents a new sentiment analysis method by combing features from text with features from image. Bigram model is applied in text fea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1653800499305ba7f96ffa60133f4db8
https://doi.org/10.1007/978-3-319-18032-8_5
https://doi.org/10.1007/978-3-319-18032-8_5