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Disambiguations
Ji Ruan [3]Jian Ruan [2]J. Ruan [1]Jujun Ruan [1]
See also
Jing Ruan
King's College London
Jun Ruan
Fudan University
  1.  70
    Action emulation.Jan Eijck, Ji Ruan & Tomasz Sadzik - 2012 - Synthese 185 (S1):131-151.
    The effects of public announcements, private communications, deceptive messages to groups, and so on, can all be captured by a general mechanism of updating multi-agent models with update action models, now in widespread use. There is a natural extension of the definition of a bisimulation to action models. Surely enough, updating with bisimilar action models gives the same result (modulo bisimulation). But the converse turns out to be false: update models may have the same update effects without being bisimilar. We (...)
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  2.  30
    Action emulation.Jan van Eijck, Ji Ruan & Tomasz Sadzik - 2012 - Synthese 185 (S1):131-151.
    The effects of public announcements, private communications, deceptive messages to groups, and so on, can all be captured by a general mechanism of updating multi-agent models with update action models, now in widespread use. There is a natural extension of the definition of a bisimulation to action models. Surely enough, updating with bisimilar action models gives the same result. But the converse turns out to be false: update models may have the same update effects without being bisimilar. We propose action (...)
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  3.  33
    Connecting dynamic epistemic and temporal epistemic logics.H. van Ditmarsch, W. van der Hoek & J. Ruan - 2013 - Logic Journal of the IGPL 21 (3):380-403.
  4. A Hybrid Fuzzy Wavelet Neural Network Model with Self-Adapted Fuzzy c-Means Clustering and Genetic Algorithm for Water Quality Prediction in Rivers.Mingzhi Huang, Hongbin di TianLiu, Chao Zhang, Xiaohui Yi, Jiannan Cai, Jujun Ruan, Tao Zhang, Shaofei Kong & Guangguo Ying - 2018 - Complexity 2018:1-11.
    Water quality prediction is the basis of water environmental planning, evaluation, and management. In this work, a novel intelligent prediction model based on the fuzzy wavelet neural network including the neural network, the fuzzy logic, the wavelet transform, and the genetic algorithm was proposed to simulate the nonlinearity of water quality parameters and water quality predictions. A self-adapted fuzzy c-means clustering was used to determine the number of fuzzy rules. A hybrid learning algorithm based on a genetic algorithm and gradient (...)
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  5.  10
    Clinical and Objective Cognitive Measures for the Diagnosis of Cognitive Frailty Subtypes: A Comparative Study.Qingwei Ruan, Weibin Zhang, Jian Ruan, Jie Chen & Zhuowei Yu - 2021 - Frontiers in Psychology 12.
    BackgroundCognitive frailty includes reversible and potentially reversible subtypes; the former is known as concurrent physical frailty and pre-mild cognitive impairment subjective cognitive decline, whereas the latter is known as concurrent PF and MCI. The diagnoses of pre-MCI SCD and MCI are based on clinical criteria and various subjective cognitive decline questionnaires. Heterogeneous assessment of cognitive impairment results in significant variability of CI, CF, and their subtype prevalence in various population-based studies.ObjectiveThis study aimed to compare the classification differences in CI and (...)
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  6.  13
    Heterogeneous Influence of Frailty Phenotypes in Age-Related Hearing Loss and Tinnitus in Chinese Older Adults: An Explorative Study.Qingwei Ruan, Jie Chen, Ruxin Zhang, Weibin Zhang, Jian Ruan, Min Zhang, Chao Han & Zhuowei Yu - 2021 - Frontiers in Psychology 11.
    BackgroundFried physical frailty, with mobility frailty and non-motor frailty phenotypes, is a heterogeneous syndrome. The coexistence of the two phenotypes and cognitive impairment is referred to as cognitive frailty. It remains unknown whether frailty phenotype has a different association with hearing loss and tinnitus.MethodsOf the 5,328 community-dwelling older adults, 429 participants aged ≥58 years were enrolled in the study. The participants were divided into robust, mobility, and non-mobility frailty, mobility and non-mobility CF, and cognitive decline [subdivided into mild cognitive impairment (...)
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  7.  34
    Logical-Epistemic Foundations of General Game Descriptions.Ji Ruan & Michael Thielscher - 2014 - Studia Logica 102 (2):321-338.
    A general game player automatically learns to play arbitrary new games solely by being told their rules. For this purpose games are specified in the general Game Description Language (GDL), a variant of Datalog with function symbols that uses a few game-specific keywords. A recent extension of basic GDL allows the description of nondeterministic games with any number of players who may have incomplete, asymmetric information. In this paper, we analyse the epistemic structure and expressiveness of this language in terms (...)
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