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PFV2: Packet fragmentation with variable size and vigorous mapping in time-sensitive networking

Journal of systems Architecture 2025年 166卷

作者： Wenyan Yan Bin Fu Dongsheng Wei Renfa Li Yixue Lei Yuhang Jia Guoqi Xie Key Laboratory for Embedded and Network Computing of Hunan Province College of Computer Science and Electronic Engineering Hunan University Changsha 410082 Hunan China Center for Convergence of Automobile and Cyberspace Research Institute of Hunan University in Chongqing Chongqing 401120 China Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems School of Computer and Artificial Intelligence Xiangnan University Chenzhou 423000 Hunan China Future Network Laboratory Tencent Beijing 100080 China

With the rapid advancement of intelligent automobiles, the ever-growing communication data put forward high bandwidth and low latency requirements. To meet these requirements, automotive Original Equipment Manufacturers (OEMs) widely adopt domain-centralized Electrical/Electronic (E/E) architecture. In this architecture, Time-Sensitive Networking (TSN) is expected to serve as the backbone network because of its high bandwidth and deterministic communication. TSN uses the Gate Control List (GCL) to divide its time length into multiple time slots, and the time intervals of these time slots are non-uniform (equal or unequal). Different flows have varying requirements for time slot sizes. To enhance the acceptance ratio of Time-Triggered (TT) flows through GCL time slot allocation, packet fragmentation (i.e., flow fragmentation) is introduced into TSN in the recent study. The state-of-the-art packet fragmentation solution divides one un-schedulable TT flow into multiple equal-sized packets (i.e., equal-sized time slots). In other words, these fixed-size packets are difficult to be mapped into the time slots with different sizes. This study develops a Packet Fragmentation with Variable-size and Vigorous-mapping (PFV2) technique based on the following three innovations: (1) we implement variable-size packet fragmentation, which iteratively divides the un-schedulable TT flow into smaller packets and then dynamically reschedules these packets; (2) we implement the vigorous mapping solution from packets to time slots by deeply searching for available time slots within the flow’s deadline; and (3) we verify PFV2 based on the LS1028A with Cortex-A72 (i.e., the NXP automotive-grade development board). PFV2 improves the acceptance ratio by up to 20.18% and bandwidth utilization by up to 7.024% compared with the state-of-the-art solution. The theoretical and practical co-verification experiments demonstrate that the PFV2 can effectively improve the flow acceptance ratio and outpe

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Regret and Cumulative Constraint Violation Analysis for Distributed Online Constrained Convex Optimization

arXiv

引用

arXiv 2021年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Chai, Tianyou Johansson, Karl H. The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden The Digital Futures Stockholm10044 Sweden The Department of Control Science and Engineering College of Electronics and Information Engineering The Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore

This paper considers the distributed online convex optimization problem with time-varying constraints over a network of agents. This is a sequential decision making problem with two sequences of arbitrarily varying convex loss and constraint functions. At each round, each agent selects a decision from the decision set, and then only a portion of the loss function and a coordinate block of the constraint function at this round are privately revealed to this agent. The goal of the network is to minimize the network-wide loss accumulated over time. Two distributed online algorithms with full-information and bandit feedback are proposed. Both dynamic and static network regret bounds are analyzed for the proposed algorithms, and network cumulative constraint violation is used to measure constraint violation, which excludes the situation that strictly feasible constraints can compensate the effects of violated constraints. In particular, we show that the proposed algorithms achieve O(T max{κ,1-κ}) static network regret and O(T 1-κ/2) network cumulative constraint violation, where T is the time horizon and κ ∈ (0, 1) is a user-defined trade-off parameter. Moreover, if the loss functions are strongly convex, then the static network regret bound can be reduced to O(T κ). Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2021, The Authors. All rights reserved.

关键词： Economic and social effects

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CLAWER: Context-aware Cloud-Fog based Workflow Management Framework for Health Emergency Services

CLAWER: Context-aware Cloud-Fog based Workflow Management Fr...

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IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGRID)

作者： Shreya Ghosh Jaydeep Das Soumya K Ghosh Rajkumar Buyya Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Advanced Technology Development Centre Indian Institute of Technology Kharagpur India Cloud Computing and Distributed Systems (CLOUDS) Lab School of Computing and Information Systems The University of Melbourne Australia

ISBN: (数字)9781728160955

ISBN: (纸本)9781728196497

With the major development of sensor technologies and advancements of communication network infrastructures, there is a growing interest to add more intelligence in the e-health monitoring for facilitating an effective healthcare system. While IoT devices are capable of continuous health-parameter sensing and providing notifications to the user, an effective business process management (BPM) facilitates effective system integration and data processing workflow. This paper proposes an efficient framework for managing emergency situations (specifically, health-related) through the analysis of heterogeneous data sources. The proposed framework, named CLAWER (CLoud-Fog bAsed Workflow for Emergency seRvice) aims to bridge the gap between process management and data analytics by providing an automated workflow for personalized health-monitoring and efficient recommendation system. Here, the IoT devices are used for collecting the movement and health data. The smart phone can act as an edge device to acquire data with user movement information. The accumulated data is initially processed inside the fog device, and finally the analysis and recommendations are generated by the cloud. In this paper the indoor health-status of the users are analysed in small cell cloud enhanced eNode B, which is used as fog device. The generated recommendations are stored in the fog device to provide the recommendations to the users with low latency and in timely manner. The experimental analysis of CLAWER yields better precision and recall values than the existing methods.

关键词： Cloud computing Roads Medical services Markov processes Monitoring Delays Biomedical monitoring

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Application-level Benchmarking of Quantum computers using Nonlocal Game Strategies

arXiv

引用

arXiv 2023年

作者： Furches, Jim Chehade, Sarah Hamilton, Kathleen Wiebe, Nathan Marrero, Carlos Ortiz College of Computing Georgia Institute of Technology AtlantaGA30332 United States Physical Detection Systems and Deployment Division Pacific Northwest National Laboratory RichlandWA99354 United States Quantum Computational Science Group Oak Ridge National Laboratory Oak RidgeTN37830 United States Department of Computer Science University of Toronto ONM5S 1A1 Canada High Performance Computing Group Pacific Northwest National Laboratory RichlandWA99354 United States Canadian Institute for Advanced Research TorontoONM5G 1M1 Canada Department of Electrical & Computer Engineering North Carolina State University RaleighNC27607 United States

In a nonlocal game, two noncommunicating players cooperate to convince a referee that they possess a strategy that does not violate the rules of the game. Quantum strategies allow players to optimally win some games by performing joint measurements on a shared entangled state, but computing these strategies can be challenging. We present a variational quantum algorithm to compute quantum strategies for nonlocal games by encoding the rules of a nonlocal game into a Hamiltonian. We show how this algorithm can generate a short-depth optimal quantum strategy for a graph coloring game with a quantum advantage. This quantum strategy is then evaluated on fourteen different quantum hardware platforms to demonstrate its utility as a benchmark. Finally, we discuss potential sources of errors that can explain the observed decreased performance of the executed task and derive an expression for the number of samples required to accurately estimate the win rate in the presence of noise. Copyright © 2023, The Authors. All rights reserved.

关键词： Hamiltonians

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On the Philosophical, Cognitive and Mathematical Foundations of Symbiotic Autonomous systems (SAS)

arXiv

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arXiv 2021年

作者： Wang, Yingxu Karray, Fakhri Kwong, Sam Plataniotis, Konstantinos N. Leung, Henry Hou, Ming Tunstel, Edward Rudas, Imre J. Trajkovic, Ljiljana Kaynak, Okyay Kacprzyk, Janusz Zhou, Mengchu Smith, Michael H. Chen, Philip Patel, Shushma University of Calgary Canada FIEEE Dept. of Electrical & Computer Engineering University of Waterloo ON Canada FIEEE Department of Computer Science City University of Hong Kong Hong Kong FIEEE Dept. of Electrical & Computer Engineering University of Toronto ON Canada SMIEEE Toronto Research Centre DRDC Canada FIEEE Autonomous & Intelligent Systems Dept. Raytheon Technologies Research Center United States Óbuda University Budapest Hungary FIEEE School of Engineering Science Simon Fraser University BurnabyBC Canada FIEEE Bogazici University Bebek Istanbul Turkey FIEEE Systems Research Institute Polish Academy of Sciences Warsaw Poland FIEEE Dept. of Computer Science New Jersey Institute of Technology NJ United States SMIEEE Furaxa Inc. OrindaCA United States FIEEE School of Computer Science and Engineering South China University of Technology Guangzhou China FBCS Faculty of Computing Engineering and Media De Montfort University LeicesterLE1 9BH United Kingdom

Symbiotic Autonomous systems (SAS) are advanced intelligent and cognitive systems exhibiting autonomous collective intelligence enabled by coherent symbiosis of human-machine interactions in hybrid societies. Basic research in the emerging field of SAS has triggered advanced general AI technologies functioning without human intervention or hybrid symbiotic systems synergizing humans and intelligent machines into coherent cognitive systems. This work presents a theoretical framework of SAS underpinned by the latest advances in intelligence, cognition, computer, and system sciences. SAS are characterized by the composition of autonomous and symbiotic systems that adopt bio-brain-social-inspired and heterogeneously synergized structures and autonomous behaviors. This paper explores their cognitive and mathematical foundations. The challenge to seamless human-machine interactions in a hybrid environment is addressed. SAS-based collective intelligence is explored in order to augment human capability by autonomous machine intelligence towards the next generation of general AI, autonomous computers, and trustworthy mission-critical intelligent systems. Emerging paradigms and engineering applications of SAS are elaborated via an autonomous knowledge learning system that symbiotically works between humans and cognitive robots. © 2021, CC BY-NC-ND.

关键词： Cognitive systems

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Observation of Declination Dependence in the Cosmic Ray Energy Spectrum

arXiv

引用

arXiv 2024年

作者： Abbasi, R.U. Abu-Zayyad, T. Allen, M. Belz, J.W. Bergman, D.R. Buckland, I. Campbell, W. Cheon, B.G. Endo, K. Fedynitch, A. Fujii, T. Fujisue, K. Fujita, K. Fukushima, M. Furlich, G. Gerber, Z. Globus, N. Hanlon, W. Hayashida, N. He, H. Hibino, K. Higuchi, R. Ikeda, D. Ishii, T. Ivanov, D. Jeong, S. Jui, C.C.H. Kadota, K. Kakimoto, F. Kalashev, O. Kasahara, K. Kawachi, Y. Kawata, K. Kharuk, I. Kido, E. Kim, H.B. Kim, J.H. Kim, S.W. Kobo, R. Komae, I. Komatsu, K. Komori, K. Koyama, C. Kudenko, M. Kuroiwa, M. Kusumori, Y. Kuznetsov, M. Kwon, Y.J. Lee, K.H. Lee, M.J. Lubsandorzhiev, B. Lundquist, J.P. Matsuzawa, A. Matthews, J.A. Matthews, J.N. Mizuno, K. Mori, M. Murakami, M. Nagataki, S. Nakahara, M. Nakamura, T. Nakayama, T. Nakayama, Y. Nonaka, T. Ogio, S. Ohoka, H. Okazaki, N. Onishi, M. Oshima, A. Oshima, H. Ozawa, S. Park, I.H. Park, K.Y. Potts, M. Przybylak, M. Pshirkov, M.S. Remington, J. Rott, C. Rubtsov, G.I. Ryu, D. Sagawa, H. Sakaki, N. Sakamoto, R. Sako, T. Sakurai, N. Sakurai, S. Sato, D. Sato, S. Sekino, K. Shibata, T. Shikita, J. Shimodaira, H. Shin, B.K. Shin, H.S. Shinozaki, K. Smith, J.D. Sokolsky, P. Stokes, B.T. Stroman, T.A. Takagi, Y. Takahashi, K. Takeda, M. Takeishi, R. Taketa, A. Takita, M. Tameda, Y. Tanaka, K. Tanaka, M. Thomas, S.B. Thomson, G.B. Tinyakov, P. Tkachev, I. Tomida, T. Troitsky, S. Tsunesada, Y. Udo, S. Urban, F. Vaiman, I.A. Vrábel, M. Warren, D. Yamazaki, K. Zhezher, Y. Zundel, Z. Zvirzdin, J. Department of Physics Loyola University Chicago ChicagoIL60660 United States High Energy Astrophysics Institute Department of Physics and Astronomy University of Utah Salt Lake CityUT84112-0830 United States Department of Physics The Research Institute of Natural Science Hanyang University Seongdong-gu Seoul426-791 Korea Republic of Graduate School of Science Osaka Metropolitan University Sugimoto Sumiyoshi Osaka558-8585 Japan Institute of Physics Academia Sinica Taipei City115201 Taiwan Institute for Cosmic Ray Research University of Tokyo Chiba Kashiwa277-8582 Japan Nambu Yoichiro Institute of Theoretical and Experimental Physics Osaka Metropolitan University Sugimoto Sumiyoshi Osaka558-8585 Japan Astrophysical Big Bang Laboratory RIKEN Saitama Wako351-0198 Japan Faculty of Engineering Kanagawa University Kanagawa Yokohama221-8686 Japan Interdisciplinary Graduate School of Medicine and Engineering University of Yamanashi Yamanashi Kofu400-8511 Japan Department of Physics Sungkyunkwan University Jang-an-gu Suwon16419 Korea Republic of Department of Physics Tokyo City University Setagaya-ku Tokyo158-8557 Japan Institute for Nuclear Research of the Russian Academy of Sciences Moscow117312 Russia Faculty of Systems Engineering and Science Shibaura Institute of Technology Minato-ku Tokyo337-8570 Japan Academic Assembly School of Science and Technology Institute of Engineering Shinshu University Nagano Nagano380-8554 Japan Graduate School of Engineering Osaka Electro-Communication University Osaka Neyagawa-shi572-8530 Japan Service de Physique Théorique Université Libre de Bruxelles Brussels1050 Belgium Department of Physics Yonsei University Seodaemun-gu Seoul120-749 Korea Republic of Center for Astrophysics and Cosmology University of Nova Gorica Nova Gorica5297 Slovenia Faculty of Science Kochi University Kochi Kochi780-8520 Japan College of Science and Engineering Chubu University Aichi Kasugai487-8501 Japa

We report on an observation of the difference between northern and southern skies of the ultrahigh energy cosmic ray energy spectrum with a significance of ∼8σ. We use measurements from the two largest experiments—the Telescope Array observing the northern hemisphere and the Pierre Auger Observatory viewing the southern hemisphere. Since the comparison of two measurements from different observatories introduces the issue of possible systematic differences between detectors and analyses, we validate the methodology of the comparison by examining the region of the sky where the apertures of the two observatories overlap. Although the spectra differ in this region, we find that there is only a 1.8σ difference between the spectrum measurements when anisotropic regions are removed and a fiducial cut in the aperture is applied. © 2024, CC BY.

关键词： Observatories

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Resilient Sparse Controller Design with Guaranteed Disturbance Attenuation

Resilient Sparse Controller Design with Guaranteed Disturban...

引用

American Control Conference (ACC)

作者： MirSaleh Bahavarnia Hossein K. Mousavi Department of Electrical and Computer Engineering Institute for Systems Research at the University of Maryland College Park MD USA Department of Mechanical Engineering and Mechanics Lehigh University Bethlehem PA USA

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

We design resilient sparse state-feedback controllers for a linear time-invariant (LTI) control system while attaining a pre-specified guarantee on H ∞ performance measure. We leverage a technique from non-fragile control theory to identify a region of resilient state-feedback controllers. Afterward, we explore the region to identify a sparse controller. To this end, we use two different techniques: the greedy method of sparsification, as well as the re-weighted 11 norm minimization. Our approach highlights a tradeoff between the sparsity of the feedback gain, performance measure, and fragility of the design. To best of our knowledge, this work is the first framework providing H ∞ performance guarantees for sparse feedback gain design.

关键词： Linear matrix inequalities Sparse matrices Robustness Symmetric matrices Attenuation Aerospace electronics Covariance matrices

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Observation of disorder-free localization and efficient disorder averaging on a quantum processor

arXiv

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arXiv 2024年

作者： Gyawali, G. Cochran, T. Lensky, Y.D. Rosenberg, E. Karamlou, A.H. Kechedzhi, K. Berndtsson, J. Westerhout, T. Asfaw, A. Abanin, D. Acharya, R. Aghababaie Beni, L. Andersen, T.I. Ansmann, M. Arute, F. Arya, K. Astrakhantsev, N. Atalaya, J. Babbush, R. Ballard, B. Bardin, J. Bengtsson, A. Bilmes, A. Bortoli, G. Bourassa, A. Bovaird, J. Brill, L. Broughton, M. Browne, D. Buchea, B. Buckley, B. Buell, D. Burger, T. Burkett, B. Bushnell, N. Cabrera, A. Campero, J. Chang, H.-S. Chen, Z. Chiaro, B. Claes, J. Cleland, A. Cogan, J. Collins, R. Conner, P. Courtney, W. Crook, A.L. Das, S. Debroy, D.M. Del Toro Barba, A. Demura, S. De Lorenzo, L. Di Paolo, A. Donohoe, P. Drozdov, I. Dunsworth, A. Earle, C. Eickbusch, A. Elbag, A. Elzouka, M. Erickson, C. Faoro, L. Fatemi, R. Ferreira, V. Flores Burgos, L. Forati, E. Fowler, A. Foxen, B. Ganjam, S. Gasca, R. Giang, W. Gidney, C. Gilboa, D. Gosula, R. Grajales Dau, A. Graumann, D. Greene, A. Gross, J. Habegger, S. Hamilton, M. Hansen, M. Harrigan, M. Harrington, S. Heslin, S. Heu, P. Hill, G. Hilton, J. Hoffmann, M. Huang, H.-Y. Huff, A. Huggins, W.J. Ioffe, L.B. Isakov, S.V. Jeffrey, E. Jiang, Z. Jones, C. Jordan, S. Joshi, C. Juhas, P. Kafri, D. Kang, H. Khaire, T. Khattar, T. Khezri, M. Kieferová, M. Kim, S. Klimov, P. Klots, A. Kobrin, B. Korotkov, A. Kostritsa, F. Kreikebaum, J. Kurilovich, V. Landhuis, D. Langley, B. Laptev, P. Lau, K.-M. Ledford, J. Lee, J. Lee, K. Lester, B. Le Guevel, L. Li, W. Lill, A. Liu, W. Livingston, W. Locharla, A. Lundahl, D. Lunt, A. Madhuk, S. Maloney, A. Mandrà, S. Martin, L. Martin, S. Martin, O. Maxfield, C. McClean, J. McEwen, M. Meeks, S. Megrant, A. Mi, X. Miao, K. Mieszala, A. Molina, S. Montazeri, S. Morvan, A. Movassagh, R. Neill, C. Nersisyan, A. Newman, M. Nguyen, A. Nguyen, M. Ni, C.-H. Ottosson, K. Pizzuto, A. Potter, R. Pritchard, O. Pryadko, L. Quintana, C. Reagor, M. Rhodes, D. Roberts, G. Rocque, C. Rubin, N. Saei, N. Google Research Mountain ViewCA United States Department of Physics Cornell University IthacaNY United States Laboratory of Solid State and Atomic Physics Cornell University IthacaNY United States Department of Physics Princeton University PrincetonNJ United States Institute of Molecules and Materials Radboud University Nijmegen Netherlands Department of Electrical and Computer Engineering University of Massachusetts AmherstMA United States Department of Physics University of Connecticut StorrsCT United States Department of Electrical and Computer Engineering Auburn University AuburnAL United States QSI Faculty of Engineering & Information Technology University of Technology Sydney NSW Australia Department of Electrical and Computer Engineering University of California RiversideCA United States Department of Chemistry and Chemical Biology Harvard University United States Department of Physics and Astronomy University of California RiversideCA United States Laboratory of Theoretical Physics and Modelling CY Cergy Paris Universite UMR CNRS 8089 Pontoise Cergy-Pontoise Cedex France Technical University of Munich TUM School of Natural Sciences Physics Department TQM Garching Germany Munich Germany Blackett Laboratory Imperial College London LondonSW7 2AZ United Kingdom Max Planck Institute of Quantum Optics Garching Germany Department of Physics Arnold Sommerfeld Center for Theoretical Physics Ludwig Maximilian University of Munich Munich Germany Max Planck Institute for the Physics of Complex Systems Dresden Germany

One of the most challenging problems in the computational study of localization in quantum many-body systems is to capture the effects of rare events, which requires sampling over exponentially many disorder realizations. We implement an efficient procedure on a quantum processor, leveraging quantum parallelism, to efficiently sample over all disorder realizations. We observe localization without disorder in quantum many-body dynamics in one and two dimensions: perturbations do not diffuse even though both the generator of evolution and the initial states are fully translationally invariant. The disorder strength as well as its density can be readily tuned using the initial state. Furthermore, we demonstrate the versatility of our platform by measuring Rényi entropies. Our method could also be extended to higher moments of the physical observables and disorder learning. © 2024, CC BY.

关键词： Quantum electronics

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Green IoT using UAVs in B5G networks: A review of applications and strategies

arXiv

引用

arXiv 2021年

作者： Alsamhi, Saeed H. Afghah, Fatemeh Sahal, Radhya Hawbani, Ammar Al-Qaness, A.A. Lee, B. Guizani, Mohsen Software Research Institute Athlone Institute of Technology Athlone Ireland IBB University Ibb Yemen School of Informatics Computing and Cyber Systems Northern Arizona University United States Hudaidah University Hudaida Yemen School of Computer Science and Technology University of Science and Technology of China Hefei China State Key Laboratory for Information Engineering in Surveying Mapping and Remote Sensing Wuhan University China Department of Computer Science and Engineering Qatar University Qatar

Recently, Unmanned Aerial Vehicles (UAVs) present a promising advanced technology that can enhance people life quality and smartness of cities dramatically and increase overall economic efficiency. UAVs have attained a significant interest in supporting many applications such as surveillance, agriculture, communication, transportation, pollution monitoring, disaster management, public safety, healthcare, and environmental preservation. Industry 4.0 applications are conceived of intelligent things that can automatically and collaboratively improve beyond 5G (B5G). Therefore, the Internet of Things (IoT) is required to ensure collaboration between the vast multitude of things efficiently anywhere in real-world applications that are monitored in real-time. However, many IoT devices consume a significant amount of energy when transmitting the collected data from surrounding environments. Due to a drone's capability to fly closer to IoT, UAV technology plays a vital role in greening IoT by transmitting collected data to achieve a sustainable, reliable, eco-friendly Industry 4.0. This survey presents an overview of the techniques and strategies proposed recently to achieve green IoT using UAVs infrastructure for a reliable and sustainable smart world. This survey is different from other attempts in terms of concept, focus, and discussion. Finally, various use cases, challenges, and opportunities regarding green IoT using UAVs are presented. © 2021, CC BY.

关键词： Energy efficiency

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From LSAT: The Progress and challenges of complex reasoning

arXiv

引用

arXiv 2021年

作者： Wang, Siyuan Liu, Zhongkun Zhong, Wanjun Zhou, Ming Wei, Zhongyu Chen, Zhumin Duan, Nan The School of Data Science Fudan University Shanghai200433 China The Research Institute of Intelligent and Complex Systems Fudan University Shanghai200433 China The School of Computer Science and Technology Shandong University Qingdao266237 China The School of Computer Science and Engineering Sun Yat-Sen University Guangzhou510275 China The Sinovation Ventures Beijing100080 China Microsoft Research Beijing100080 China

Complex reasoning aims to draw a correct inference based on complex rules. As a hallmark of human intelligence, it involves a degree of explicit reading comprehension, interpretation of logical knowledge and complex rule application. In this paper, we take a step forward in complex reasoning by systematically studying the three challenging and domain-general tasks of the Law School Admission Test (LSAT), including analytical reasoning, logical reasoning and reading comprehension. We propose a hybrid reasoning system to integrate these three tasks and achieve impressive overall performance on the LSAT tests. The experimental results demonstrate that our system endows itself a certain complex reasoning ability, especially the fundamental reading comprehension and challenging logical reasoning capacities. Further analysis also shows the effectiveness of combining the pre-trained models with the task-specific reasoning module, and integrating symbolic knowledge into discrete interpretable reasoning steps in complex reasoning. We further shed a light on the potential future directions, like unsupervised symbolic knowledge extraction, model interpretability, few-shot learning and comprehensive benchmark for complex reasoning. © 2021, CC BY.

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