Computer Science ›› 2019, Vol. 46 ›› Issue (12): 220-230.doi: 10.11896/jsjkx.190800129

• Artificial Intelligence • Previous Articles     Next Articles

A Survey of Automated Negotiation and Its Fuzzy Set Based Models

LUO Xu-dong1, HUANG Qiao-juan1, ZHAN Jie-yu2   

  1. (College of Computer Science and Information Engineering,Guangxi Normal University,Guilin,Guangxi 541000,China)1;
    (School of Computer Science,South China Normal University,Guangzhou 510631,China)2
  • Received:2019-05-27 Online:2019-12-15 Published:2019-12-17

Abstract: Negotiation is a process in which two or more interested parties communicate with each other for an agreement,automated negotiation isto use artificial intelligence system to automate this process.This paper first discussed the significance of studying automated negotiation.At the national level,the research and development of such systems is consistent with the national AI development strategy of China.It can not only help people live a better life in the e-commerce era,but also reduce corruption by using computer systems instead of manual negotiation.Secondly,the deve-lopment of negotiation proceeds in game theory,management science and computer science were outlined.The Nobel laureate in economics,Nash,started the study of negotiation in the field of game theory.However,the biggest problem in such study is the assumption that all information of negotiating parties involved is essentially public,which is unrealistic.Therefore,researchers in management science focus on how to conduct manual negotiation when all information of all parties is not disclosed.In general,manual negotiation is inefficient and difficult,and often fails to achieve optimal results.As a result,computer scientists are trying to replace manual negotiate with madnines.At the beginning,they focused on the computer-to-computer automated negotiation.Now their focus is turning to computer-to-human automated negotiation.Finally,methods of using fuzzy logic and fuzzy constraints to develop intelligent agents for automated negotiation were summarised.This paper focused on the application of these two fuzzy methods in the automatic negotiation system and the practical application of fuzzy automatic negotiation system.

Key words: Automated negotiation, Artificial intelligence, Electronic commerce, Intelligent agent, Fuzzy logic, Fuzzy constraint, Machine learning

CLC Number: 

  • TP18
[1] LI S.The sales of double 11 reached 314.3 billion,making it the biggest shopping carnival in the world [EB/OL].(2018-11-12) [2019-09-13].
[2] TENG F F.China’s e-commerce transactions amounted to 31.63 trillion,ranking first in the world [EB/OL].(2019-08-05) [2019-09-13]. 9/429898.shtml.
[3] ZHANG D D.Fabulously rich! Guangdong’s GDP is approaching 100 billion.What’s the global level [EB/OL].(2019-01-28) [2019-09-12].
[4] LUO X D,JENNINGS N R,SHADBOLT N,et al.A fuzzy constraint based model for bilateral,multi-issue negotiations in semi-competitive environments [J].Artificial Intelligence,2003,148(1/2):53-102.
[5] JENNINGS N R,FARATIN P,LOMUSCIO A R,et al.Automated negotiation:Prospects,methods and challenges [J].Group Decision and Negotiation,2001,10(2):199-215.
[6] LUO X D,MIAO C,JENNINGS N R,et al.KEMNAD:A knowledge engineering methodology for negotiating agent development [J].Computational Intelligence,2012,28(1): 51-105.
[7] NASH J F.The bargaining problem [J].Econometrica,1953, 18(2):155-162.
[8] KALAI E,SMORODINSKY M.Other solutions to Nash’s bargaining problem [J].Econometrica,1975,43(3):513-518.
[9] RUBINSTEIN A.Perfect equilibrium in a bargaining model [J].Econometrica,1982,50(1):97-109.
[10] LI Y T,YUAN J.The test of experimental economics on bargaining theory [J].Commercial Research,2013,55(3):186-191.
[11] DU S F,ZHU J A,GAO D,et al.Optimal decision-making for Nash bargaining fairness concerned newsvendor in two-level supply chain [J].Journal of Management Sciences in China,2013,16(3):67-72.
[12] CHEN J,HUANGFU H Y,LI H.The right cognition effect in bargaining game decision-making [J].Journal of Psychological Science,2012,35(3):647-653.
[13] RAIFFA H.The art and science of negotiation [M]//The Belknap Press of Harvard University Press,1982:2-15.
[14] FISHER R,URY W,PATTON B.Getting to yes:Negotiating agreement without giving in [M]//Getting to Yes Negotiating Agreement Without Giving in.New York:Penguin Books,2011:10-25.
[15] ADAIR W L,TAYLOR M S,TINSLEY C H.Starting out on the right foot:Negotiation schemas when cultures collide [J].Negotiation and Conflict Management Research,2009,2(2):138-163.
[16] MITTAL M,GABA D,RANA H,et al.An Optimized Multi-item Bilateral Negotiation Model [C]//2019 Amity International Conference on Artificial Intelligence.2019:566-570.
[17] THOMAS C J.An alternating-offers model of multilateral negotiations [J].Journal of Economic Behavior & Organization,2018,149:269-293.
[18] GAO T,HUANG M,WANG Q,et al.A systematic model of stable multilateral automated negotiation in e-market environment[J].Engineering Applications of Artificial Intelligence,2018,74:134-145.
[19] REN F,ZHANG M,LUO X D,et al.A parallel,multi-issue negotiation model in dynamic e-markets [C]//Advances in Artificial Intelligence.Lecture Notes in Computer Science(AI 2011).2011,7106:442-451.
[20] ALRAYES B,KAFALI Ö,STATHIS K.Concurrent bilateral negotiation for open e-markets:the CONAN strategy [J].Knowledge and Information Systems,2018,56(2):463-501.
[21] NIU L,REN F,ZHANG M.Feasible Negotiation Procedures for Multiple Interdependent Negotiations [C]//Proceedings of the 17th International Conference on Autonomous Agents and Multi- Agent Systems.2018:641-649.
[22] PAN L,LUO X D,MENG X,et al.A two-stage win-win multi attribute negotiation model:Optimization and then concession [J].Computational Intelligence,2013,29(4):577-626.
[23] LUO X D,YANG Y F,LEUNG H F.Reward and penalty functions in automated negotiation [J].International Journal of Intelligent Systems,2016,31(7):637-672.
[24] DIMOPOULOS Y,MAILLY J G,MORAITIS P.Argumentation- based negotiation with incomplete opponent profiles [C]//Proceedings of the 18th International Conference on Autonomous Agents and Multiagent Systems.2019:1252-1260.
[25] BECHERU A,BADICA C.Augmenting multi-agent negotiation in interconnected freight transport using complex networks analysis [C]//Computational Science - ICCS 2019. Lecture Notes in Computer Science,2019,11537:434-448.
[26] O’HALLORAN J.An automated negotiation system for ecommerce store owners to enable flexible product pricing [D].Ireland:Technological University Dublin,2019.
[27] PINTO A,PINTO T,SILVA F,et al.Automated combination of bilateral energy contracts negotiation tactics [C]//2018 IEEE Power & Energy Society General Meeting (PESGM).2018:1-5.
[28] XIA W.Interdependent order allocation in the many-to-many supply chain using automated negotiation [D].Wuhan:Huazhong University of Science &Technology,2018.
[29] YANG C,SUN J.Research on negotiation of manufacturing enterprise supply chain based on multi-agent [J].Journal of Internet Technology,2019,20(2):389-398.
[30] HUANG M M,YUAN J J,CAO L.NSGAII Based Automated Negotiation in Collaborative Product Development Project [J].Operations Research and Management Science,2017(3):90-95,103.
[31] ORTEGA A P,MERRETT G V,RAMCHURN S D.Automated negotiation for opportunistic energy trading between neighbouring wireless sensor networks [C]//2018 IEEE Internatio-nal Conference on Communications,Control,and Computing Technologies for Smart Grids.2018,1-6.
[32] SAID F B,ALIMI A M.MOANOFS:Multi-objective automated negotiation based online feature selection system for big data classification [EB/OL].(2018-10-11) [2019-10-08].
[33] BAARSLAG T,ALAN A T,GOMER R,et al.An automated negotiation agent for permission management [C]//Proceedings of the 16th Conference on Autonomous Agents and Multi-Agent Systems.2017:380-390.
[34] GUPTA S,VASARDANI M,LOHANI B,et al.Pedestrian’s risk-based negotiation model for self-driving vehicles to get the right of way [J].Accident Analysis & Prevention,2019,124:163-173.
[35] WONG P N.Who has the right of way,automated vehicles or drivers?:Multiple perspectives in safety,negotiation and trust [C]//Proceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications.2019:198-210.
[36] CHATER N,MISYAK J,WATSON D,et al.Negotiating the traffic:can cognitive science help make autonomous vehicles a reality? [J].Trends in cognitive sciences,2018,22(2):93-95.
[37] GAO J,WONG T,WANG C.Coordinating patient preferences through automated negotiation:A multiagent systems model for diagnostic services scheduling [J].Advanced Engineering Informatics,2019,100934:42.
[38] JOHNSON E,LUCAS G,KIM P,et al.Intelligent Tutoring System for Negotiation Skills Training [M]//Artificial Intelligence in Education.Lecture Notes in Computer Science,Cham:Springer,2019.
[39] BOUYAKOUB F M H,BELKHIR A,BELKACEMNACER A,et al.An E-negotiation agent for an e-tourism platform [J].International Journal of Web Services Research,2019,16(2):65-87.
[40] ESHRAGH F,POOYANDEH M,MARCEAU D J.Automated negotiation in environmental resource management:Review and assessment [J].Journal of environmental management,2015,162:148-157.
[41] YUAN L,CHEN S,ZHANG Z.A novel strategy for complex human-agent negotiation [C]//Proceedings of the 13th CCF Conference on Computer Supported Cooperative Work and Social Computing.Singapore:Springer,2019,917:67-76.
[42] VAHIDOV R,SAADE R,YUB B.The effects of interplay between negotiation tactics and task complexity in software agent to human negotiations [J].Electronic Commerce Research and Applications,2017,26:50-61.
[43] FRANZONI V,MILANI A,VALLVERDU J,et al.Emotional affordances in human-machine interactive planning and negotiation [C]//Proceedings of the International Conference on Web Intelligence.2017:924-930.
[44] ROTHMAN N B,NORTHCRAFT G B.Unlocking integrative potential:Expressed emotional ambivalence and negotiation outcomes [J].Organizational Behavior and Human Decision Processes,2015,126:65-76.
[45] KLEEF VAN G A,DREU DE C K,MANST- EAD A S.The interpersonal effects of anger and happiness in negotiations [J].Journal of KPersonality and Social Psychology,2004,86(1):57-76.
[46] ADAM H,SHIRAKO A,MADDUX W W.Cultural variance in the interpersonal effects of anger in negotiations [J].Psycholo-gical Science,2010,21(6):882-889.
[47] KLEEF VAN G A,DREU DE C K W,MANSTEAD A S R.Supplication and appeasement in conflict and negotiation:the interpersonal effects of disappointment,worry,guilt,and regret [J].Journal of Personality and Social Psychology,2006,91(1):124-142.
[48] HARELI S,DAVID S,HESS U.The effect of the negotiator’s social power as a function of the counterpart’s emotional reactions in a computer mediated negotiation [J].Europe’s Journal of Psychology,2013,9(4):1-99.
[49] GALINSKY A D,GRUENFELD D H,MAGEE J C.From power to action [J].Journal of Personality and Social Psychology,2003,85(3):453-466.
[50] KELTNER D,GRUENFELD D H,ANDERSON C.Power,approach,and inhibition [J].Psychological Review,2003,110:265-284.
[51] LEE M,LUCAS G,MELL J,et al.What’s on your virtual mind?:Mind perception in human-agent negotiations [C]//Proceedings of the 19th ACM International Conference on Intelligent Virtual Agents.2019:38-45.
[52] 罗旭东,杨彧锋,伍桂花.博弈的哲学[M].广州:中山大学出版社,2014:91-105.
[53] KIM E,GIMBEL S I,LITVINOVA A,et al.Predicting decision in human-agent negotiation using functional MRI [C]//Proceedings of the 38th Annual Meeting of the Cognitive Science Society.2016:1-5.
[54] KIM E,GILBERT J,HOROWITZ C,et al.Decoding partner type in Human-Agent negotiation using functional MRI [C]//Proceedings of the 39th Annual Meeting of the Cognitive Science Society.2017:12-23.
[55] ADAM M T,TEUBNER T,GIMPEL H.No rage against the machine:How computer agents mitigate human emotional processes in electronic negotiations [J].Group Decision and Negotiation,2018,27(4):543-571.
[56] CAO M,LUO X D,LUO X R,et al.Automated negotiation for e-commerce decision making:A goal deliberated agent architecture for multi-strategy selection [J].Decision Support Systems,2015,73:1-14.
[57] HAIM G,AKOV Y,KRAUS S,et al.A Cultural Sensitive Agent for Human-Computer Negotiation [C]//Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems.2012,1:451-458.
[58] HAIM G,NISIM D,TSATKIN M.Human-Computer agent negotiation using cross culture reliability models [C]//Conflict Resolution in Decision Making, Lecture Notes in Artificial Intelligence.2016,10238:118-133.
[59] HAIM G,AN B,KRAUS S.Human-computer negotiation in a three player market setting [J].Artificial Intelligence,2017,246:34-52.
[60] MELL J,BEISSINGER M,GRATCH J.An Expert-Model & Machine Learning Hybrid Approach to Predicting Human-Agent Negotiation Outcomes [C]//Proceedings of the 19th ACM International Conference on Intelligent Virtual Agents.2019:212-214.
[61] BAARSLAG T,HENDRIKX M J,HINDRIKS K V,et al. Learning about the opponent in automated bilateral negotiation:a comprehensive survey of opponent modeling techniques [J].Autonomous Agents and Multi-Agent Systems,2016,30(5):849-898.
[62] ESHRAGH F,SHAHBAZI M,FAR B.Real-time opponent learning in automated negotiation using recursive Bayesian filtering [J].Expert Systems with Applications,2019,128:28-53.
[63] RODRIGUEZ-FERNANDEZ J,PINTO T,SILVA F,et al.Context aware Q-learning-based model for decision support in the negotiation of energy contracts [J].International Journal of Electrical Power & Energy Systems,2019,104:489-501.
[64] AYDOGAN R,MARSA-MAESTRE I,KLEIN M,et al.A machine learning approach for mechanism selection in complex negotiations [J].Journal of Systems Science and Systems Engineering,2018,27(2):134-155.
[65] KROHLING D E,CHIOTTI O,MARTINEZ E.The importance of context-dependent learning in negotiation agents [J].Artificial Intelligence,2019,22(63):135-149.
[66] KOLOMVATSOS K,ANAGNOSTOPOULOS C,HADJIEF- THYMIADES S.A fuzzy logic system for bargaining in information markets [J].ACM Transactions on Intelligent Systems and Technology,2012,3(2):1-26.
[67] ZUO B H,SUN Y.Fuzzy logic to support bilateral agent negotiation in e-commerce [C]//Proceedings of the 2009 International Conference on Artificial Intelligence and Computational Intelligence.2009,4:179-183.
[68] KOLOMVATSOS K,TRIVIZAKIS D,HADJI EFTHYMIA- DES S.An adaptive fuzzy logic system for automated negotiations [J].Fuzzy Sets and Systems,2015,269(C):135-152.
[69] ARAPOGLOU R,KOLOMVATSOS K,HADJIEFTHYMIADES S.Buyer agent decision process based on automatic fuzzy rules generation methods [C]//Proceedings of 2010 IEEE International Conference on Fuzzy Systems.2010:1-8.
[70] FRANCISCO M,MEZQUITA Y,REVOLLAR S,et al.Multi-agent distributed model predictive control with fuzzy negotiation [J].Expert Systems with Applications,2019,129:68-83.
[71] ZHANG L,ZHENG P E,RAO G Z.Multi-agent negotiation:An approach based on fuzzy logic control [J].Journal of Computer Applications,2006,26(11):2648-2650.
[72] ZHANG L L,LIU Q.Bilateral automated negotiation based on fuzzy method with incomplete information [J].Journal of Guangxi Normal University,2015,33(4):38-42.
[73] COSTANTINO F,GRAVIO G D.Multistage bilateral bargaining model with incomplete information:A fuzzy approach [J].International Journal of Production Economics,2009,117(2):235-243.
[74] YAHIA W B,AYADI O,MASMOUDI F.A fuzzy-based negotiation approach for collaborative planning in manufacturing supply chains [J].Journal of Intelligent Manufacturing,2015,28(8):1-20.
[75] ADABI S,MOVAGHAR A,RAHMANI A M,et al.A new fuzzy negotiation protocol for grid resource allocation [J].Journal of Network and Computer Applications,2014,37(39):89-126.
[76] HABERLAND V,MILES S,LUCK M. Adjustable Fuzzy Inference for Adaptive Grid Resource Negotiation [M]//Next Frontier in Agent-based Complex Automated Negotiation.2015:37-57.
[77] RAJAVEL R,IYER K,MAHESWAR R,et al.Adaptive neuro-fuzzy behavioral learning strategy for effective decision making in the fuzzy-based cloud service negotiation framework [J].Journal of Intelligent & Fuzzy Systems,2019,36(3):2311-2322.
[78] SHOJAIEMEHR B,RAHMANI A M,QADER N N.Cloud computing service negotiation:A systematic review [J].Computer Standards & Interfaces,2018,55:196-206.
[79] HE M H,LEUNG H F,JENNINGS N R.A fuzzy-logic based bidding strategy for autonomous agents in continuous double auctions [J].IEEE Transactions on Knowledge and Data Engineering,2003,15(6):1345-1363.
[80] KAUR P,GOYAL M,LU J.A comparison of bidding strategies for online auctions using fuzzy reasoning and negotiation decision functions [J].IEEE Transactions on Fuzzy Systems,2016:25(2):425-438.
[81] CARBO J,MOLINA J,DAVILA J.Reaching agreements through fuzzy counter-offers [C]//Proceedings of International Conference on Web Engineering.2003:90-93.
[82] SHOJAIEMEHR B,RAFSANJANI M K.Erratum to:A suppl- ier offer modification approach based on fuzzy systems for automated negotiation in ecommerce [J].Information Systems Frontiers,2016,21(1):161.
[83] SHOJAIEMEHR B,RAFSANJANI M K.A supplier offer modification approach based on fuzzy systems for automated negotiation in e-commerce [J].Information Systems Frontiers,2018,20(1):143-160.
[84] VOLKMER T,METZGER O,SPENGLER T,et al. An extended fuzzy approach to multicriteria modelling of bilateral bargaining [M]//Multikriterielle Optimierung undEntscheidungsunter-stützung.2019:89-105.
[85] YU M,ZHAI Y Q.A Fuzzy logic based asking strategy for sel- ler agents in e-commerce [J].Computer Engineering and Applications,2004,40(15):201-205.
[86] CHENG C B,CHAN C H,LIN C C.Buyer-supplier negotiation by fuzzy logic based agents [C]//Proceedings of the 3rd International Conference on Information Technology and Applications.2005:137-142.
[87] ZHAN J Y,LUO X D,FENG C,et al.A multi-demand negotiation model based on fuzzy rules elicited via psychological experiments [J].Applied Soft Computing,2017,67:840-864.
[88] YANG Y F,LUO X D. A Multi-demand negotiation model with fuzzy concession strategies [C]//ICAISC 2019:Artificial Intelligence and Soft Computing.Lecture Notes in Computer Science,2019,11509:689-707.
[89] BAKKER J,HAMMOND A,BLOEMBERGEN D,et al.RL- BOA:A Modular Reinforcement Learning Framework for Autonomous Negotiating Agents [C]//Proceedings of the 18th International Conference on Autonomous Agents and Multi Agent Systems.2019:260-268.
[90] ZHAN J,LUO X D.Adaptive conceding strategies for negotiating agents based on interval type-2 fuzzy logic [C]//Procee-dings of the 2016 International Conference on Knowledge Science.2016:222-235.
[91] KOLOMVATSOS K,HADJIEFTHYMIADES S.Implicit deadline calculation for seller agent bargaining in information marketplaces [C]//Proceedings of the 2008 International Conference on Complex.2008:184-190.
[92] KOLOMVATSOS K,HADJIEFTHYMIADES S.Automatic fuzzy rules generation for the deadline calculation of a seller agent [C]//Proceedings of International Symposium on Autonomous Decentralized System.2009:1-6.
[93] LI J Y,WU Y Y.Research on adaptive ANS based on fuzzy inference [J].Microcomputer Information,2009,25(24):166-167.
[94] MENDEL J M,JOHN R I B.Type-2 fuzzy sets made simple [J].IEEE Transactions on Fuzzy Systems,2002,10(2):117-127.
[95] CASTILLO O,MELIN P.Type-2 Fuzzy Logic:Theory and Applications [C]//2007 IEEE International Conference on Granular Computing (GRC 2007).2007:145.
[96] COLLOBERT R,WESTON J,BOTTOU L,et al.Natural Language Processing (Almost) from Scratch [J].Journal of Machine Learning Research,2011,12(8):2493-2537.
[97] RUTTKAY Z.Fuzzy constraint satisfaction [C]//Proceedings of IEEE Conference on Evolutionary Computing.1994:1263-1268.
[98] LUO X D,LEE H M,LEUNG H F,et al.Prioritised fuzzy constraint satisfaction problems:axioms,instantiation and validation [J].Fuzzy Sets and Systems,2003,136(2):151-188.
[99] OKUHARA S,ITO T.A compromising strategy based on constraint relaxation for automated negotiating agents [C]//Trends in Artificial Intelligence,Lecture Notes in Computer Science(PRICAI 2019).2019,11670:675-687.
[100] ZHAN J Y,LUO X D,JIANG Y.An Atanassov intuitionistic fuzzy constraint based method for offer evaluation and trade-off making in automated negotiation [J].Knowledge-Based Systems,2018,139:170-188.
[101] CHEN L,QIU Y H,ZHANG Q.Fuzzy constraint-based model for multiple concurrent bilateral negotiations [J].Journal of Computer Applications,2007,27(12):2906-2898.
[102] HAN H W,ZHENG W P.An PFCSP-based automatic negotia- tion model on B2C transaction [J].Journal of Northeast Normal University,2012,44(4):56-60.
[103] HAN W.Automatic negotiation system based on fussy con- straint programming [J].Computer Engineering and Applications,2006,44(3):94-97.
[104] LÓPEZ-CARMONA M A,VELASCO J R.An expressive approach to fuzzy constraint based agent purchase negotiation [C]//Proceedings of the 5th International Joint Conference on Autonomous Agents and Multiagent Systems.2006:429-431.
[105] LÓPEZ-CARMONA M A,VELASCO J R,MARSA-MAE- STRE I.The agents’ attitudes in fuzzy constraint based automated purchase negotiations [C]//Proceedings of the 5th International Central and Eastern European Conference on Multi-agent Systems and Applications.2007:246-255.
[106] ATANASSOV K T.Intuitionistic fuzzy sets:Theory and Applications [M]//Studies in Fuzziness and Soft Computing,Physica,Heidelberg,1999,35:15-36.
[107] YAGER R R.Pythagorean fuzzy subsets [C]//Proceedings of Joint IFSA World Congress and NAFIPS Annual Meeting.2013:57-61.
[108] YAGER R R.Properties and Applications of Pythagorean Fuzzy Sets [C]//Imprecision and Uncertainty in Information Representation and Processing.Studies in Fuzziness and Soft Computing,2016,332:119-136.
[109] SENAPATI T,YAGER R R.Fermatean fuzzy sets [J].Journal of Ambient Intelligence and Humanized Computing,2019(S1):1-12.
[110] LIU D,LIU Y,CHEN X.Fermatean fuzzy linguistic set and its application in multicriteria decision making [J].International Journal of Intelligent Systems,2019,34(5):878-894.
[111] YAGER R R,Rybalov A.Uninorm aggregation operators [J].Fuzzy Sets and Systems,1996,80(1):111-120.
[112] LUO X D,JENNINGS N R.A spectrum of compromise aggregation operators for multi-attribute decision making [J].Artificial Intelligence,2007,171(2/3):161-184.
[113] GARG,HARISH.A new generalized Pythagorean fuzzy information aggregation using Einstein operations and its application to decision making [J].International Journal of Intelligent Systems,2016,31(9):886-920.
[114] WEI G,LU M.Pythagorean fuzzy power aggregation operators in multiple attribute decision making [J].International Journal of Intelligent Systems,2018,33(1):169-186.
[115] JANA C,SENAPATI T,PAL M,et al.Picture fuzzy Dombi aggregation operators:Application to MADM process [J].Applied Soft Computing,2019,74:99-109.
[116] LI L,YEO C S,HSU C Y,et al.Agent-based fuzzy constraint-directed negotiation for service level agreements in cloud computing [J].Cluster Computing,2018,21(2):1349-1363.
[117] LI L,LAI K R,ZHU S.Data-Driven Behavior-Based Negotiation Model for Cyber-Physical-Social Systems [J].IEEE Access,2019,7:83319-83331.
[118] LAI K R,LIN M W,YU T J.Learning opponent’s beliefs via fuzzy constraint-directed approach to make effective agent negotiation [J].Applied Intelligence,2010,33(2):232-246.
[119] HSU C Y,KAO B R,HO V L,et al.Agent-based fuzzy constraint-directed negotiation mechanism for distributed job shop scheduling [J].Engineering Applications of Artificial Intelligence,2016,53:140-154.
[120] HSU C Y,KAO B R,HO V L,et al.An agent-based fuzzy constraint-directed negotiation model for solving supply chain planning and scheduling problems [J].Applied Soft Computing,2016,48:703-715.
[121] RUTTKAY Z.Fuzzy constraint satisfaction [C]//Proceedings of IEEE Conference on Evolutionary Computing.1994:1263-1268.
[122] HUANG Q J,LUO X D.State-of-art and development trend of artificial intelligence combined with law [J].Computer Science,2018,45(12):1-11.
[1] LI Yin, LI Bi-xin. Memory Leak Test Acceleration Based on Script Prediction and Reconstruction [J]. Computer Science, 2020, 47(9): 31-39.
[2] DING Yu, WEI Hao, PAN Zhi-song, LIU Xin. Survey of Network Representation Learning [J]. Computer Science, 2020, 47(9): 52-59.
[3] SU Chang, ZHANG Ding-quan, XIE Xian-zhong, TAN Ya. NFV Memory Resource Management in 5G Communication Network [J]. Computer Science, 2020, 47(9): 246-251.
[4] WANG Hui, LE Zi-chun, GONG Xuan, WU Yu-kun, ZUO Hao. Review of Link Prediction Methods Based on Feature Classification [J]. Computer Science, 2020, 47(8): 302-312.
[5] YUAN Ye, HE Xiao-ge, ZHU Ding-kun, WANG Fu-lee, XIE Hao-ran, WANG Jun, WEI Ming-qiang, GUO Yan-wen. Survey of Visual Image Saliency Detection [J]. Computer Science, 2020, 47(7): 84-91.
[6] PENG Wei, HU Ning and HU Jing-Jing. Overview of Research on Image Steganalysis Algorithms [J]. Computer Science, 2020, 47(6A): 325-331.
[7] BAO Zhen-shan, GUO Jun-nan, XIE Yuan and ZHANG Wen-bo. Model for Stock Price Trend Prediction Based on LSTM and GA [J]. Computer Science, 2020, 47(6A): 467-473.
[8] REN Yi. Design of Network Multi-server SIP Information Encryption System Based on Block Chain and Artificial Intelligence [J]. Computer Science, 2020, 47(6A): 634-638.
[9] ZHU Lin-li, HUA Gang, GAO Wei. Stability Analysis of Ontology Learning Algorithm in Decision Graph Setting [J]. Computer Science, 2020, 47(5): 43-50.
[10] ZHAO Cheng, YE Yao-wei, YAO Ming-hai. Stock Volatility Forecast Based on Financial Text Emotion [J]. Computer Science, 2020, 47(5): 79-83.
[11] WANG Guo-yin, QU Zhong, ZHAO Xian-lian. Practical Exploration of Discipline Construction of Artificial Intelligence+ [J]. Computer Science, 2020, 47(4): 1-5.
[12] WANG Xiao-ming,ZHAO Xin-bo. Survey of Construction and Application of Reading Eye-tracking Corpus [J]. Computer Science, 2020, 47(3): 174-181.
[13] ANG Wei-yi,BAI Chen-jia,CAI Chao,ZHAO Ying-nan,LIU Peng. Survey on Sparse Reward in Deep Reinforcement Learning [J]. Computer Science, 2020, 47(3): 182-191.
[14] CAO Feng,XU Yang,ZHONG Jian,NING Xin-ran. First-order Logic Clause Set Preprocessing Method Based on Goal Deduction Distance [J]. Computer Science, 2020, 47(3): 217-221.
[15] JIAN Song-lei, LU Kai. Survey on Representation Learning of Complex Heterogeneous Data [J]. Computer Science, 2020, 47(2): 1-9.
Full text



[1] LEI Li-hui and WANG Jing. Parallelization of LTL Model Checking Based on Possibility Measure[J]. Computer Science, 2018, 45(4): 71 -75 .
[2] SUN Qi, JIN Yan, HE Kun and XU Ling-xuan. Hybrid Evolutionary Algorithm for Solving Mixed Capacitated General Routing Problem[J]. Computer Science, 2018, 45(4): 76 -82 .
[3] ZHANG Jia-nan and XIAO Ming-yu. Approximation Algorithm for Weighted Mixed Domination Problem[J]. Computer Science, 2018, 45(4): 83 -88 .
[4] WU Jian-hui, HUANG Zhong-xiang, LI Wu, WU Jian-hui, PENG Xin and ZHANG Sheng. Robustness Optimization of Sequence Decision in Urban Road Construction[J]. Computer Science, 2018, 45(4): 89 -93 .
[5] SHI Wen-jun, WU Ji-gang and LUO Yu-chun. Fast and Efficient Scheduling Algorithms for Mobile Cloud Offloading[J]. Computer Science, 2018, 45(4): 94 -99 .
[6] ZHOU Yan-ping and YE Qiao-lin. L1-norm Distance Based Least Squares Twin Support Vector Machine[J]. Computer Science, 2018, 45(4): 100 -105 .
[7] LIU Bo-yi, TANG Xiang-yan and CHENG Jie-ren. Recognition Method for Corn Borer Based on Templates Matching in Muliple Growth Periods[J]. Computer Science, 2018, 45(4): 106 -111 .
[8] CUI Qiong, LI Jian-hua, WANG Hong and NAN Ming-li. Resilience Analysis Model of Networked Command Information System Based on Node Repairability[J]. Computer Science, 2018, 45(4): 117 -121 .
[9] WANG Zhen-chao, HOU Huan-huan and LIAN Rui. Path Optimization Scheme for Restraining Degree of Disorder in CMT[J]. Computer Science, 2018, 45(4): 122 -125 .
[10] YANG Yu-qi, ZHANG Guo-an and JIN Xi-long. Dual-cluster-head Routing Protocol Based on Vehicle Density in VANETs[J]. Computer Science, 2018, 45(4): 126 -130 .