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... ACP approach is firstly initialized by Fei-Yue Wang in 2004 to deal with social computing [9,53,55]. It consists of artificial societies (A) for modeling, computational experiments (C) for analysis, and parallel execution (P) for control [30,61]. ...
... ACP approach is proposed to better deal with social computing [4,9,59]. ACP = Artificial societies + Computational experiments + Parallel execution. ...
... By ACP approach, modeling with artificial societies shows promise for this problem. By artificial societies, we can treat computers as social laboratories, then evaluate and quantitatively analyze various factors in social-computing problems [9]. In our ACP approach-based recommender system, we want to train a parallel environment that can generate the expectation of the future state. ...
Recommender systems aim to suggest the items which can best fit the needs of the users and thus play an important role in online services. To get a satisfactory recommendation, some researchers model the recommendation procedure as a Markov decision process where the recommender is the agent and the users are the environment. Then, they use reinforcement learning to perform the recommendation by sharing the browsing histories of different users. However, when the number of users is large, there will be much noise in the sharing process, limiting the ability of reinforcement learning to generate a satisfactory recommendation. ACP approach is proposed to deal with social computing by learning a parallel system from the real system. There can be less noise in the parallel system than that in the real system with an effective learning process, thus the ACP approach has the potential to address the noise in the recommendation. In this paper, we combine the ACP approach into the reinforcement learning based recommender system to deal with the noise and thus improve the recommendation. Firstly, based on the ACP approach, we train a parallel environment of the real environment. Then we use the trained parallel environment to predict the future state in the Markov decision process of the recommender system. There will be less noise in the predicted states than that in the original states, since the output of our parallel environment is effectively learned by the expectation of the future state in the deep neural network. Finally, instead of the original states, we use the predicted states to generate the recommendation list in the reinforcement learning for the recommendation. In this way, the generated recommendation list can be better with less noise from the states. The theoretical analysis and the experiment illustrate that our recommender system can better perform the recommendation than existing recommender systems.
... This also calls for novel frameworks in connected autonomous driving. Motivated by this, the parallel driving, a cloud-based cyber-physical-social systems (CPSS) framework has been developed and implemented in multiple real-world driving scenarios [3,11]. ...
... Human involvements and social characteristics impose an additional dimension to traditional cyber-physical systems (CPS), which leads to the framework of CPSS [1][2][3]. Rapid Digital Quadruplets for Cyber-Physical-Social Systems based Parallel Driving: From Concept to Applications Teng Liu, Xing Yang, Hong Wang, Xiaolin Tang, Long Chen, Huilong Yu, Fei-Yue Wang development in artificial intelligence, big data, and communication technologies enables development of CPSS to attract more and more attention in recent years. The integration of critical elements in the CPSS contain the physical, mental and artificial worlds. ...
... The ACP method means the artificial societies (A), computational experiments (C) and parallel execution (P), which was proposed by Fei-Yue Wang since 2004 [3][4][5][6]. To describe concisely, A is usually used for modeling the complex systems, C is applied to calculate and analyze the responses and P is utilized for control and management. ...
Digital quadruplets aiming to improve road safety, traffic efficiency, and driving cooperation for future connected automated vehicles are proposed with the enlightenment of ACP based parallel driving. The ACP method denotes Artificial societies, Computational experiments, and Parallel execution modules for cyber-physical-social systems. Four agents are designed in the framework of digital quadruplets: descriptive vehicles, predictive vehicles, prescriptive vehicles, and real vehicles. The three virtual vehicles (descriptive, predictive, and prescriptive) dynamically interact with the real one in order to enhance the safety and performance of the real vehicle. The details of the three virtual vehicles in the digital quadruplets are described. Then, the interactions between the virtual and real vehicles are presented. The experimental results of the digital quadruplets demonstrate the effectiveness of the proposed framework.
... They try to design various concepts or architectures to make full use of the digital world and make it to serve the real world better. For example, digital twin [13], parallel system [14] and parallel driving [15], as well as DVE architecture here, mention the interactions of physical world and digital world. Digital twin is a digital description of the physical twin and is usually used to simulate some complicated tasks. ...
... Digital twin is a digital description of the physical twin and is usually used to simulate some complicated tasks. Parallel theory is a computational theory of complex social-economic systems [14] while parallel driving is its application in the driving field. The framework, parallel driving, aims at synergizing connected automated driving through the interactions between mental world, which contains human's cognition, and artificial world, which includes vehicles' decisions [15]. ...
... Due to the essential model intractability and the lack of high-quality data in online RTB markets, it is quite difficult to validate our proposed model with online field experiments. Fortunately, with the help of computational experiments approach [13], we can design experiment scenarios to evaluate our model and analysis. In this section, we will utilize the computational experiment approach to validate the effect of market segmentation on the total revenue, and identify the optimal segmentation granularity for maximizing the advertisers' and the DSP's revenues. ...
Real Time Bidding (RTB) is an emerging business model and a popular research topic of online advertising markets. Using cookie-based big-data analysis, RTB advertising platforms have the ability to precisely identify the features and preferences of online users, segment them into various kinds of niche markets, and thus achieve the precision marketing via delivering advertisements to the best-matched users. The segmentation granularity used by such platforms, typically referred to as the Demand Side Platforms (DSPs), plays a central role in the effectiveness and efficiency of the RTB ecosystem. In practice, fine-grained user segmentations may lead to increased value-per-clicks and bid prices from advertisers, but at the same time reduced competition and possibly decreased bid prices in each niche market. This motivates our research on the optimal segmentation granularity to solve this dilemma faced by DSPs. Using a RTB market model with two-stage resales, we analyzed DSPs' segmentation strategies taking the revenues of both advertisers and DSPs into consideration. We also validated our proposed model and analysis using the computational experiment approach, and the experimental results indicate that with the increasing of segmentation granularity, the weighted sum of the DSP and advertisers' revenues tends to first rise and then decline in all weight-value cases, and the optimal granularity is greatly influenced by the value of weights. Our work highlights the need for DSPs of moderately using, instead of overusing, the online big data for maximized revenues.
... It monitors, simulates, diagnoses, predicts, and controls the formation process and behavior of products in the real environment. The parallel system theory was proposed by Prof. Fei-Yue Wang for management and control of complex systems [16]. The first definition of digital twin was made by Michael Grieves for presenting product life cycle management (PLM). ...
Fused deposition modelling (FDM) 3D printing, as a supporting technology in social manufacturing and cloud manufacturing, is a rapidly growing technology in the era of industry 4.0. It produces objects with a layer-by-layer material accumulation technique. However, qualitative uncertainties are the common challenges yet. In order to assure print quality, studying the error causing parameters and minimizing their effects are important. This paper presents a feedback-based error compensation strategy, which integrates a fuzzy inference system and a grey wolf optimization algorithm. The objectives are twofold. First, the possible errors in FDM 3D printing are discussed in detail and optimal error causing parameters are obtained in percentage. This is used to understand the effects of the printing errors in every phase of the 3D printing process. From the nine optimization configuration trials used, Config-6 that has 100 number of iterations and 60 wolves is selected due to its higher convergence speed and best fitness value. The integral absolute error (IAE) is used as an objective function and the global minimum is achieved in the iteration interval 86,100\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\left [ {86,100} \right ]$\end{document}. The outputs of this optimization problem are used to achieve the next objective. Second, a closed-loop quality monitoring approach comprising of inner-loops and an outer-loop is taken. The three inner-loops are used to monitor the errors during pre-printing, printing, and post-printing, respectively. The outer-loop, on the other hand, is responsible for monitoring the aggregated errors in all the three 3D printing phases. The error compensation system simulation in Matlab is run for 10 s, and the results show that the “normal” range deformation factors are reached within less than 2 s for the inner-loops, whereas the outer-loop deformation factor is achieved within 2 s. The responses are within the acceptable time range.
... The parallel system theory was proposed for control and management of the complex systems based on Artificial systems, Computational experiments, and Parallel execution (ACP) method [11], [12], [13], which provides a promising way to overcome the difficulties of modeling, analysis, control and experiments of complex systems with characteristics of inseparability and unpredictability. Over the past decade, ACPbased parallel system theory has been applied in many areas such as public health [14], emergency evacuation [15], [16], service management [17], and transportation [18], [19], which has shown excellent performances compared to the traditional methods for the control and management of complex systems. ...
... some never happened scenes or disaster scenes). Compared with traditional methods, the computational experiment method has several obvious advantages, such as accurate control, easy operation, and repeatable execution [31][32][33]. By far, the computational experiment method has been widely used in analysis and prediction of complex social system, such as social-economic system [34], pathological system [35], traffic system [36], war simulation system [37], physiological /political ecosystem [38], etc. ...
Internet business can be divided into two categories: pure online business and Online to Offline (O2O) business. Currently, the recommendation technology for online business is maturing, such as news, movies, products, and so forth. However, traditional recommendation technology can easily cause the overcrowding at some O2O services because of the big data traps. In the end, the users' experience with the O2O service recommendation is useless or very poor because they have to wait for a long time and can't enjoy the service immediately. Hence, how to improve the performance of O2O service recommendation has become a vital problem. To solve the problem, this paper proposes a research framework based on the continuous feedback learning mechanism between cyber layer and social layer. Then, the continuous feedback ideas are implemented in the design of the O2O service recommendation strategy step by step. Furthermore, the computational experiment system is constructed to perform performance analysis of these service strategies. The results show that our research framework is conductive to help O2O service recommendation to escape the big-data traps and to improve user experience.
... The ACP method means the artificial societies (A), computational experiments (C) and parallel execution (P), which was presented by Fei-Yue Wang since 2004 [1][2][3][4]. Especially, A is usually used for modeling the complex systems, C is applied to calculate and analyze the responses and P is utilized for control and management. These three components of ACP can be mapped into three parallel worlds that are called physical, mental and artificial worlds, as shown in Fig. 1. ...
Parallel driving is a novel framework to synthesize vehicle intelligence and transport automation. This article aims to define digital quadruplets in parallel driving. In the cyber-physical-social systems (CPSS), based on the ACP method, the names of the digital quadruplets are first given, which are descriptive, predictive, prescriptive and real vehicles. The objectives of the three virtual digital vehicles are interacting, guiding, simulating and improving with the real vehicles. Then, the three virtual components of the digital quadruplets are introduced in detail and their applications are also illustrated. Finally, the real vehicles in the parallel driving system and the research process of the digital quadruplets are depicted. The presented digital quadruplets in parallel driving are expected to make the future connected automated driving safety, efficiently and synergistically.
... In this section, we utilize the computational experiment approach [7] to evaluate our proposed model. Our experimental evaluation focuses on the following two purposes. ...
Real time bidding (RTB) is emerged with the rapid development and integration of Internet and big data, and it has become the most important business model for online computational advertising. In RTB-based advertising markets, Demand Side Platforms (DSPs) aim to help the advertisers buy ad impressions matched with their target audiences. Due to the existence of discount rate, the advertising effect may be diminished when displaying the advertisements multiple times to the same target audience. As such, frequency capping is widely considered as a crucial issue faced by most advertisers. In this paper , we mainly consider the frequency capping problems in RTB advertising markets, and establish a two-stage optimization model for advertisers and DSPs. Utilizing the computational experiment approach, we design two experiments to validate our model. The experimental results show that under different discount rates, the optimal frequency caps are different. Moreover, when considering all the discount rates, there exists an optimal frequency cap, at which the expected maximum revenue can be obtained in the long run.
... 引言 [7] 。通过构造与实际系统对应的软件定义模型--人工系统，通过在线 学习、离线计算、虚实互动，使得人工系统成为可试验的"社会实验室"，以计算实验的方 式为实际系统的运行主动提供动态的，在线的"借鉴"、"预估"和"引导"。 平行系统框架图如图 1 所示，主要分为实际系统和人工系统两部分。简单来讲，人工系 统是对实际系统的软件化定义，不仅是对实际系统的数字化"仿真"，也是为实际系统运行 提供可替代版本（或其他可能的情形），包括模型库，算法库，开放架构体系，现代软件技 术等；实际系统即是实际生活中的真实存在的系统，具有社会复杂性、工程复杂性等特征。 通过计算实验平台，对实际系统抽象建模为人工系统，再通过人工系统反馈指导实际系统， 进行全面而系统的综合评估分析，两个系统平行互动，最终实现行为、信息、模拟、决策和 执行一体化，为复杂的实际系统的管理与控制提供高效、可靠、适用的科学决策和指导。 图 1 平行系统框架 ACP 方法是基于平行系统解决复杂系统问题的指导方法，是人工社会（Artificial societies）、计算实验（Computational experiments）与平行执行（Parallel execution） 三部分的有机组合 [8] 。人工系统可视为对原求解空间以及求解方法的拓展，基于人工系统的 建模方法有很多，如数值仿真器，物理仿真器，代理模型 [9] ，以及概率图模型等等 [10] 。在构 建人工系统的过程中，除了应与实际系统保持一致性，还需要保证高速计算、部署简单、交 互性强、 扩展灵活等特性。 计算实验结合实际系统采集到的数据， 在人工系统建模的基础上， 利用多种智能算法，进行可控实验，针对多重世界或多重网络，构成复杂多元、自底向上涌 现生成的计算实验方法， [11] 并且评估和定量分析各种实验因素，对模型进行实时性地计算、 优化。平行执行通过建立虚、实系统的闭环反馈，实时双向交互，平行执行。基于 ACP 的平 行系统可以将复杂系统的计算、分析、优化进行从离线到在线，从静态到动态，从被动到主 动的转变，进而更好的实现复杂系统的管理与控制。 [14] 平行智能车（PAVE 车） [15] 的主要目标即为实现 "车内简单，远端智能，车路互动，多车协同，平行操控"，以达到可靠性与成本之间的有 效权衡。 [16] ...
With the development of economy, traffic accidents, congestion and pollution are becoming increasingly serious. As one of the research hotspots, self-driving is becoming an effective way to solve the above problems. However, considering the high cost and unsure safety, complete self-driving still cannot be widely used. In this paper, in order to achieve a good trade-off between the safety and cost, PArallel VEhicles (PAVE) based on Cyber-Physical-Social Systems (CPSS) are proposed. Based on Artificial societies, Computational experiments
... Due to the essential complexity of online RTB markets, it is difficult or even impossible to validate our proposed model and strategies with online field experiments. Fortunately, computational experiments [4] can serve as an alternative way. In this section, we will design the experimental environment with the computational experiment approach, to validate our model. ...
Real Time Bidding (RTB) is a novel business model of online computational advertising with the integration of Internet economy and big data analysis. It can help advertisers achieve the precision marketing through the market segmentation strategies of Demand Side Platforms (DSPs). Based on a mathematical programming approach, this paper studied DSPs' strategies for market segmentation, and established a selection model of the granularity for segmenting RTB advertising markets. We proposed to validate our model using the computational experiment approach, and the experimental results show that: 1) with the increasing refinement of the market segmentation granularity, the total revenue has a tendency of a rise first followed by a decline; 2) the optimal granularity of market segmentation will be significantly influenced by the number of advertisers on the DSP, but less influenced by the number of ad requests. Our findings show the crucial role of market segmentation on the RTB advertising effect, and indicate that the DSPs should adjust their market segmentation strategies according to their total number of advertisers. Our findings also highlight the importance of advertisers as well as the characteristics of the target audiences in DSPs' market segmentation decisions. Keywords-real time bidding; computational advertising; market segmentation; demand side platforms; computational experiment
... In this section, we utilize the computational experiment approach [7] to evaluate our proposed model. Our experimental evaluation focuses on the following two purposes. ...
Benefited from the high-speed development of Internet and the popularization of big data technology, Real Time Bidding (RTB) emerged and developed quickly, and has become one of the most important and popular model for online computational advertising. In the pay-per-impression based RTB advertising, frequency capping is undoubtedly one of the most crucial issues faced by advertisers and Demand Side Platforms (DSPs), since there are generally vast amount of ad requests in RTB markets, among which many may be triggered by the same target audience. As such, choosing the optimal frequency cap considering all the advertisers becomes a critical issue faced by DSPs. Considering that displaying one advertisement multiple number of times to the same user will diminish the advertising effect, we introduce the concept of discount factor and establish an optimization model of frequency capping to seek for the optimal frequency cap for each advertiser. We also design some experiments to validate our proposed model by utilizing the computational experiment approach, and the experimental results show that the optimal frequency cap can be influenced by the values of the discount factors, and higher value of the discount factor can deduce the advertising effect of larger frequency cap. Moreover, when the discount factors of the advertisers take different values, there also exists an optimal frequency cap, at which the advertisers can get the expected maximum revenue in the long run.
... One possible path from B 2 ITS to PtMS is shown in Fig.5. The blockchain-based PtMS follows the research framework of ACP approach, namely Artificial societies + Computational experiments + Parallel execution [28] . In the "A" part, all ITS entities in physical space, including IoT devices, vehicles and assets, can be easily digitalized via "blockchain of things" and registered into blockchain, while online transportation big data in cyber-space can also be integrated into blockchain. ...
Blockchain, widely known as one of the disruptive technologies emerged in recent years, is experiencing rapid development and has the full potential of revolutionizing the increasingly centralized intelligent transportation systems (ITS) in applications. Blockchain can be utilized to establish a secured, trusted and decentralized autonomous ITS ecosystem, creating better usage of the legacy ITS infrastructure and resources, especially effective for crowdsourcing technology. This paper conducts a preliminary study of Blockchain-based ITS (B 2 ITS). We outline an ITS-oriented, seven-layer conceptual model for blockchain, and on this basis address the key research issues in B 2 ITS. We consider that blockchain is one of the secured and trusted architectures for building the newly developed parallel transportation management systems (PtMS) , and thereby discuss the relationship between B 2 ITS and PtMS. Finally, we present a case study for blockchain-based realtime ride-sharing services. In our viewpoint, B 2 ITS represents the future trend of ITS research and practice, and this paper is aimed at stimulating further effort and providing helpful guidance and reference for future research works.
... Fei-Yue Wang first developed the parallel theory in 2004 [128]. The construction of a parallel system requires the ACP approach as the background knowledge, which is the combination of Artificial society, Computational experiments, and Parallel execution [129]. Fig. 7. Architecture of ACP-based parallel driver intention inference system. ...
Intelligent vehicles and advanced driver assistance systems (ADAS) need to have proper awareness of the traffic context as well as the driver status since ADAS share the vehicle control authorities with the human driver. This study provides an overview of the ego-vehicle driver intention inference (DII), which mainly focus on the lane change intention on highways. First, a human intention mechanism is discussed in the beginning to gain an overall understanding of the driver intention. Next, the ego-vehicle driver intention is classified into different categories based on various criteria. A complete DII system can be separated into different modules, which consists of traffic context awareness, driver states monitoring, and the vehicle dynamic measurement module. The relationship between these modules and the corresponding impacts on the DII are analyzed. Then, the lane change intention inference (LCII) system is reviewed from the perspective of input signals, algorithms, and evaluation. Finally, future concerns and emerging trends in this area are highlighted.
... The main reasons are as follows: 1) the model built in normal situations is no longer suitable for the simulations of crowd evacuation in the disasters; 2) it makes the controlled experiments not feasible for data collection because of moral and ethical considerations, and the field observations become much more difficult than that in normal situations; and 3) the behaviors and characteristics of pedestrian flows are much more complex and unpredictable in a disaster situations, especially in a state of panic. The parallel system theory was proposed for complex system control and management based on the artificial systems, computational experiments, and parallel execution approach [63]- [65], [65], which provides a promising way to get out this dilemma. It was used to explore crowd evacuation behaviors and evaluate evacuation strategies in the case of fire at the subway station and high-rise building [66], [67]. ...
This paper focuses on the bibliographic analyses and collaboration patterns in the field of pedestrian and evacuation dynamics (PED) research covering the period of 1991-2017. The statistic analyses of most productive authors, institutions, countries/regions, and cited papers, as well as keywords and their trends, are conducted based on the data set collected from the Web of Science. The most productive and high-impact authors, institutions, and countries are identified. The results of bibliographic analyses show that Europe researchers dominate and guide the research of PED in that it not only has the most papers but also has six out of the ten most-cited papers. Helbing Dirk is an influential author in the research of PED field in that he has five out of the ten most-cited papers. Chinese institutions account for 70% of the top 10 most productive institution and three among the top 5 ranks. Meanwhile, researchers from China and USA have published nearly half of the papers in this field. In addition, we generate four networks, i.e., coauthorship network, coinstitution network, cocountry/region network, and document cocitation network to analyze collaboration patterns and evolution of PED research at different levels. The software of Citespace is adopted to visualize the topological interactions among authors, institutions, and countries/regions as well as document cocitations. The degree, betweenness, burst, and PageRank are selected and measured as indicators to identify the key nodes. Finally, some future directions are put forward. The results of this paper provide a better understanding of patterns, trends, and other important factors as a basis for directing research activities, sharing knowledge, and collaborating in the field of PED research.
... This has led to a phenomenon called economic complexity (Chen 2017;Kuznets 1995). According to the advocates of this paradigm shift, complexity science is capable of understanding market economy and trade at a different level Fei-Yue (2004), as it has successfully played its role in related domains (Mitchell 2009;Phelan 2001). ...
The complexity science, with the help of, agent based modeling has recently claimed that the free market economy is producing wealth inequality—a totally opposite perception, which is in practice for more than 10 decades. It is capable of investigating the distribution of money in the market economy and finding solution for unfair gap between the wealth and, thus, overcoming poverty. This paper is an attempt to investigate this claim. This work is inspired from Gooding’s work and it, therefore, reproduces his toy trader model, which claims to offer a fair trading environment. This model is extended towards a more human-oriented economy by introducing two possible biases: the variation of market visibility between the traders (by introducing the social networks of traders) and monopoly. The basic aim was to find out the impact of market visibility and monopoly on wealth distribution and poverty. It was learnt through simulations performed, in NetLogo, that the accessibility of traders, when taken as an important factor of a free market economy, positively influences wealth disparity, wealth gap and controls poverty. However, more human-oriented economy, in fact, widens the rich-poor divide and increases poverty. These results suggest that the authorities must control the market and everyone involved in trading should be given equal opportunities. This would also help in controlling the possible monopoly of the traders. The intrinsic physics of the free market would, otherwise, will always result in an unequal distribution of wealth.
... However, the correct prediction and effective prevention of unconventional emergencies is a focus of emergency management that cannot be ignored. To solve this problem, Wang proposed the parallel computing theory for complex systems in 2004 [18]. Based on the viewpoint of multiple worlds, he proposed an artificial social model which is parallel and consistent with the real emergency system in terms of scale, behavior mode, and system characteristics. ...
The outbreak of unconventional emergencies leads to a surge in demand for emergency supplies. How to effectively arrange emergency production processes and improve production efficiency is significant. The emergency manufacturing systems are typically complex systems, which are difficult to be analyzed by using physical experiments. Based on the theory of Random Service System (RSS) and Parallel Emergency Management System (PeMS), a parallel simulation and optimization framework of production processes for surging demand of emergency supplies is constructed. Under this novel framework, an artificial system model paralleling with the real scenarios is established and optimized by the parallel implementation processes. Furthermore, a concrete example of mask shortage, which occurred at Huoshenshan Hospital in the COVID-19 pandemic, verifies the feasibility of this method.
... where [t 0 , t f ] denotes the given time horizon, is the fuel consumption rate, λ is a large positive weighting factor (λ=10000 in this paper) to restrict the terminal value of SOC, and SOC ref is a pre-allocated constant to guarantee the charge sustaining constraint [27]. ...
As a complex and critical cyber-physical system ( CPS ), the hybrid electric powertrain is significant to mitigate air pollution and improve fuel economy. Energy management strategy ( EMS ) is playing a key role to improve the energy efficiency of this CPS. This paper presents a novel bidirectional long short-term memory ( LSTM ) network based parallel reinforcement learning ( PRL ) approach to construct EMS for a hybrid tracked vehicle ( HTV ). This method contains two levels. The high-level establishes a parallel system first, which includes a real powertrain system and an artificial system. Then, the synthesized data from this parallel system is trained by a bidirectional LSTM network. The lower-level determines the optimal EMS using the trained action state function in the model-free reinforcement learning ( RL ) framework. PRL is a fully data-driven and learning- enabled approach that does not depend on any prediction and predefined rules. Finally, real vehicle testing is implemented and relevant experiment data is collected and calibrated. Experimental results validate that the proposed EMS can achieve considerable energy efficiency improvement by comparing with the conventional RL approach and deep RL.
In this paper, the current network experiment platforms are investigated, introduced and compared. The most popularly used simulator and its main advantages and disadvantages are demonstrated. To solve the problem of lacking flexibility and service capability of traditional network experiment platforms, based on the parallel network architecture, the corresponding computational experiment platform is proposed. The proposed platform is data-oriented, and by using the computational experiments and analysis, an optimized control strategy can be continuously updated and tracked, thus the self optimization of network systems is achieved. In the end, a computational experiment based on retweet analysis of Wechat Moments is proposed, and the effectiveness of this method is evaluated.
Energy internet (EI) is a complex coupled multienergy system; it is essential to investigate its multienergy dispatching optimization issues. To this end, this paper first proposes a novel conception of smart dispatching for EI with a complex cyber‐physical‐social system (CPSS) network from the perspective of parallel dispatch, called parallel dispatching robot (PDR), and investigates the implementations of PDR based on smart artificial society (SAS) modeling. First, we introduce EI and describe the dispatching issues of EI. Second, we discuss several important concepts supporting the parallel dispatch conception of EI, including knowledge automation (KA), CPSS, and parallel machine learning (PML). On the basis of these, we elaborate the concept of parallel dispatch. Moreover, we construct a large closed‐loop feedback control framework of parallel dispatch for EI integrating a CPSS network based on KA and PML. Third, we establish an experimental platform for PDR research based on the proposed parallel dispatch framework. Fourth, we develop the PML‐based SAS models of a single PDR in centralized dispatching modes and group PDRs in decentralized dispatching modes to achieve crowd wisdom emergence and performance improvement in current cyber‐physical system frameworks of EI. Moreover, we design an external global closed loop for PDR to evaluate its operation stability. Lastly, we conduct a detailed discussion on PDR and offer some prospects for its engineering implementations. The biggest innovation of this paper lies in systematically proposing the smart dispatching concept and framework for complex CPSS‐based EI from the perspective of parallel dispatch and thoroughly investigating how to use SAS modeling to implement parallel dispatching and control for EI considering human and social factors, which is a major extension and theoretical improvement to existing single smart wide area robot concept and a preliminary attempt in investigating a shift from Energy 4.0 to Energy 5.0 in China. We first systematically propose a novel smart dispatching framework for energy internet with complex cyber‐physical‐social systems from the perspective of parallel dispatch, called parallel CPSS framework. This framework is developed for the parallel dispatching of multienergy coupled energy internet with a complex CPSS structure represented by a new generation of energy and electric power systems. In this framework, the proposed parallel dispatching robots are employed to simulate human dispatcher group considering human and social factors (eg, the energy markets).
With the rapid development of cryptocurrency and its underlying blockchain technologies, platforms such as Ethereum and Hyperledger began to support various types of smart contracts. Smart contracts are computer protocols intended to digitally facilitate, verify, or enforce the negotiation or performance of a contract. Smart contracts have broad range of applications, such as financial services, prediction markets and Internet of Things (IoT), etc. However, there are still many challenges such as security issues and privacy disclosure that await future research. In this paper, we present a comprehensive overview on blockchain powered smart contracts. First, we give a systematic introduction for smart contracts, including the basic framework, operating mechanisms, platforms and programming languages. Second, application scenarios and existing challenges are discussed. Finally, we describe the recent advances of smart contract and present its future development trends, e.g., parallel blockchain. This paper is aimed at providing helpful guidance and reference for future research efforts.
Welcome to the fourth issue of the IEEE Transactions on Computational Social Systems (TCSS), which includes 16 regular papers and a brief discussion on social computing. We would also like to inform you that IEEE will conduct its regular 5-year review for TCSS at its TAB meeting in November at Boston. Any suggestions for our review report are welcome!
The decentralized autonomy is not a new concept, the self-organization phenomenon in natural ecosystems, the cyber movement organizations on the Internet, and the distributed artificial intelligence, etc., can all be regarded as its early manifestations. In recent years, the rapid development of block chain technology has spawned the emergence of the so-called decentralized autonomous organization (DAO), which is a new organization form that the management and operational rules are typically encoded on block chain in the form of smart contracts, and can autonomously operate without centralized control or third-party intervention. Therefore, DAO is expected to become a new and effective organization to deal with uncertain, diverse and complex environments. Defining the conception and features is the first priority. Furthermore , the five layer structural model of DAO analyzing frame to analyze typical Aragon model was proposed and the current issues as well as the research direction in future were discussed, hoping to provide significant guidance and reference for following researchers.
In view of the current research situation and the urgent demand for unmanned mines, the end-to-end parallel autonomous mining solution was proposed based on the ACP method in this paper. The research status of unmanned mining transportation system was analyzed. The basic framework of parallel autonomous mining was designed. The parallel
autonomous mining are mainly composed of four parts: the management and control center for autonomous mining, the autonomous transportation platform of truck, the autonomous mining/shovel platform and the remote take-over platform.
The 7 key technologies for realizing parallel autonomous mining system were discussed, namely, the virtual parallel mine construction, environment perception and localization, unmanned control for single equipment, collaborative。
This paper proposes a new solution for end-to-end autonomous mining operations: Internet of Things (IoT) based parallel mining, consisting of the concept definition, the solution given and the concrete realization. The proposed parallel mining is inspired by the ACP (artificial societies (A) for modeling, computational experiments (C) for analysis, and parallel execution (P) for control) approach. The basic framework of parallel mining is given and its advantages are expounded. Then the solution of parallel mining is proposed, which is mainly composed of four parts: the management and control center for autonomous mining, the autonomous transportation platform of truck, the semi-autonomous mining / shovel platform, and the remote take-over platform. Key technologies of IoT based parallel mining are discussed in detail, namely, network communication, virtual parallel mining construction, mining environment perception over-the-horizon for the moving area and obstacle detection, collaborative decision-making, planning and control for unmanned mining equipment, parallel taking-over and remote control. Finally, the performance of IoT based parallel mining, including fusion perception, collaborative decision-making, planning and control, are evaluated. The realization of parallel mining can fundamentally improve the safety of personnel and equipment, reduce the cost of mining operation and increase the production rate.
As a new FinTech innovation regulation tool, regulatory sandbox effectively balances financial innovation and risk, so it is adopted by many regulatory authorities around the world. However, until now, regulatory sandbox is still at the stage of manually submitting data, and artificial intelligence has not been applied to it. Hence, in this paper, we propose the framework of Parallel FinTech Regulatory Sandbox based on the ACP approach (Artificial systems + Computational experiments + Parallel execution). Then, we talk about how to combine the emerging blockchain technology with intelligent regulatory sandbox, thus solving problems such as poor data flow and regulation sluggish. This paper is aimed at providing helpful guidance and reference for the development of FinTech regulatory sandbox.
Blockchain Technology (BT) is blank in the construction industry. This paper introduces the basic concepts of technology of Building Information Modeling (BIM) and BT technology, combining the technical difficulties and management difficulties in the process of design, construction, operation and maintenance of buildings, and in order to provide the proposes of the following solutions: In the design stage, BIM’s three-dimensional model was used to integrate with the time and space information of the main materials, components, and products of the building, combined with BT technology, to realize dynamic and real-time management of building information at a low cost. In the construction phase, the use of BT technology to manage the supply chain information flow, instead of logs, records, etc. which depends on the personal means in the construction supervision, to improve the technical level of construction project management, to reduce the quality of man-made and safety risks, to ensure that the construction process material files are not tampered with. BT smart contract management can reduce intermediate subcontracting and project costs. In the operation and maintenance phase, information on building renovations, equipment maintenance, and other changes will be updated through BT and BIM technologies in a timely manner to guarantee that construction assets are updated on a timely basis. This paper uses the literature research method to review domestic and foreign research literatures on BT and project management, to explore new methods of construction project management, and to promote industry progress. This will not only save new tenants’ decoration costs, but also improve equipment maintenance efficiency and quality. The combination of BT and BIM technology will bring about a number of changes in project management technology in the construction industry and improve the overall technical level of the industry.
Digital quadruplets aiming to improve road safety, traffic efficiency, and driving cooperation for future connected automated vehicles are proposed with the enlightenment of ACP-based parallel driving. The ACP method denotes artificial societies, computational experiments, and parallel execution modules for cyberphysical-social systems. Four agents are designed in the framework of digital quadruplets: descriptive vehicles, predictive vehicles, prescriptive vehicles, and real vehicles. The three virtual vehicles (descriptive, predictive, and prescriptive) dynamically interact with the real one to enhance the safety and performance of the real vehicle. The details of the three virtual vehicles in the digital quadruplets are described. Then, the interactions between the virtual and real vehicles are presented. The experimental results of the digital quadruplets demonstrate the effectiveness of the proposed framework.
Welcome to the new issue of IEEE Transactions on Computational Social Systems (TCSS). First, I would like to share the news of my resignation from the position of Editor-in-Chief (EiC) due to my new position as the Vice President (VP) for Human Machine Systems of the IEEE Systems, Man, and Cybernetics Society (SMCS). SMCS requires its Transactions EiC to have no membership in its Executive Committee or Board of Governors (BoG). In 2017, I offered my resignation from the BoG in order to be the EiC of TCSS, and now I need to resign my EiC position since I have been elected as SMCS’s VP in the end of 2019. Thank you all for this extremely valuable three-and-half year experience in a field I truly love and enjoy, but it is time to let new leadership to lead TCSS to a new level of quality and excellence. A call for new EiC was announced by VP for Publication at the end of May, and I am happy to inform you that, by the deadline of June 10, seven scholars from North America, Europe, and Asia have been recommended for the EiC position. A decision will be made by the Selection Committee in July and I will announce the result in the next issue.
Welcome to the second issue of IEEE Transactions on Computational Social Systems (TCSS) this year. First of all, I would like to report that, as of this March, the
CiteScore
of TCSS has reached to 5.15, a historic high, especially considering the fact that the numbers of published articles had increased significantly in the last two years. Congratulations and thanks to all of you, for your professional support and dedication.
This paper analyzes the characteristics and challenges of the new generation smart dispatch systems, and proposes the framework of smart dispatch. Secondly, the development of the new generation artificial intelligence technology is represented, especially the development of machine learning algorithms. Thirdly, the applications of machine learning in power systems, e.g. smart generation control, optimal power flow, security assessment, smart dispatch, are listed. Finally, the framework of dispatching robot technology based on parallel learning is present.
The concept, basic framework, methodology and applications of parallel city were presented in this paper. The parallel city is an application of ACP-based parallel intelligence in city fields. The real city is running with its equivalent, and the artificial city is in virtual space, in a parallel and interactive way. The artificial city has the descriptive, predictive, and prescriptive functions on the real city. There is a closed-loop workflow between the real city and the artificial city, which iteratively optimizes the urban systems, leading to a new paradigm of intelligent urban management.
As a new form of manufacturing industry in cloud environment, social manufacturing has its inherent “social–cyber” complexity: the source of enterprise services is social, and this sociality aggravates the diversity, uncertainty and dynamics of service supply. Researchers have done a lot to improve the adaptability of service matching strategies. However, it is difficult or even impossible to for traditional methods to evaluate the viability of these strategies because of the “social–cyber” complexity. This poses new challenges to how to evaluate and optimize these strategies in a complex social manufacturing environment. Aiming at the problem, this paper proposes a computational experiment-based evaluation framework, which can simulate all kinds of actual scenarios to verify the performance of service matching strategies. This method includes three parts: (1) design of supply & demand matching strategy; (2) construction of computational experiment system; (3) performance evaluation of service strategies in different experiment environments. A case study is given to verify the applicability of our method by means of comparing several adaptive service matching strategies (supply-oriented, demand-oriented, initial supply & demand-oriented, optimized supply & demand-oriented) in two kinds of market environments. The results demonstrate that our method has a substantial promise.
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