Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Shiguang Yue"'
Publikováno v:
Discrete Dynamics in Nature and Society, Vol 2017 (2017)
Multiagent goal recognition is a tough yet important problem in many real time strategy games or simulation systems. Traditional modeling methods either are in great demand of detailed agents’ domain knowledge and training dataset for policy estima
Externí odkaz:
https://doaj.org/article/bc67c9fced804383984269a5c1d7199b
Publikováno v:
Discrete Dynamics in Nature and Society, Vol 2016 (2016)
Multiagent goal recognition is important in many simulation systems. Many of the existing modeling methods need detailed domain knowledge of agents’ cooperative behaviors and a training dataset to estimate policies. To solve these problems, we prop
Externí odkaz:
https://doaj.org/article/b297a543c2c44bc68269570856d8373b
Publikováno v:
Discrete Dynamics in Nature and Society, Vol 2017 (2017)
Multiagent goal recognition is a tough yet important problem in many real time strategy games or simulation systems. Traditional modeling methods either are in great demand of detailed agents’ domain knowledge and training dataset for policy estima
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8926f8e3a0adbec7c31b88cf930b57f8
https://doi.org/10.1155/2017/4580206
https://doi.org/10.1155/2017/4580206
Publikováno v:
Mathematical Problems in Engineering, Vol 2016 (2016)
Recognizing destinations of a maneuvering agent is important in real time strategy games. Because finding path in an uncertain environment is essentially a sequential decision problem, we can model the maneuvering process by the Markov decision proce
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::576ed018d1aedd842c3a447172ecdb8e
Publikováno v:
Discrete Dynamics in Nature and Society, Vol 2016 (2016)
Multiagent goal recognition is important in many simulation systems. Many of the existing modeling methods need detailed domain knowledge of agents’ cooperative behaviors and a training dataset to estimate policies. To solve these problems, we prop
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b36495fb9aaf0dcf9143690fd8238483
Publikováno v:
2015 IEEE International Conference on Mechatronics and Automation (ICMA).
The Logical hidden Markov model (LHMM) is a combination of the first-order logic and the hidden Markov Model (HMM). As a branch of statistical relational learning, the LHMM is of great potential in many fields. In this paper, we combine the logical d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9e7270f5056bb54ffe37c7f1c76a38ac
https://doi.org/10.1109/icma.2015.7237458
https://doi.org/10.1109/icma.2015.7237458
Publikováno v:
2015 IEEE International Conference on Mechatronics and Automation (ICMA).
Recognizing the destination of a moving agent is quite significant in many systems such as real time strategy games. Probabilistic graphical models are widely used to solve this problem, but existing models cannot recognize the changeable destination
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::adf651e451cce89f121f404c741a6c6b
https://doi.org/10.1109/icma.2015.7237608
https://doi.org/10.1109/icma.2015.7237608
Publikováno v:
Discrete Dynamics in Nature and Society, Vol 2015 (2015)
Intention recognition is significant in many applications. In this paper, we focus on team intention recognition, which identifies the intention of each team member and the team working mode. To model the team intention as well as the world state and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3975d751d009655e0d3219c1a57c7d1f
Publikováno v:
SIMULTECH
Intention recognition (IR) is significant for creating humanlike and intellectual agents in simulation systems. Previous widely used probabilistic graphical methods such as hidden Markov models (HMMs) cannot handle unstructural data, so logical hidde
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::328d11f7bffeaabc7321ef2712bfc5ee
https://doi.org/10.5220/0005036707010708
https://doi.org/10.5220/0005036707010708
Publikováno v:
2013 10th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP).
Activity recognition is challenging and valuable in both real and virtual world. As important directed graphical models, hidden Markov models and their extensions are widely used to solve probabilistic activity recognition problems. In this paper, lo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60081dd3cb8b8ddc98ad1098f7759079
https://doi.org/10.1109/iccwamtip.2013.6716604
https://doi.org/10.1109/iccwamtip.2013.6716604