{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T16:19:23Z","timestamp":1771345163374,"version":"3.50.1"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T00:00:00Z","timestamp":1771286400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T00:00:00Z","timestamp":1771286400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["22H03641"],"award-info":[{"award-number":["22H03641"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"name":"JST FOREST","award":["JPMJFR216S"],"award-info":[{"award-number":["JPMJFR216S"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Auton Agent Multi-Agent Syst"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1007\/s10458-026-09733-z","type":"journal-article","created":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T15:47:07Z","timestamp":1771343227000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["An efficient Bayesian learning-based opponent model considering parametric interrelation in automated bilateral multi-issue negotiation"],"prefix":"10.1007","volume":"40","author":[{"given":"Shengbo","family":"Chang","sequence":"first","affiliation":[]},{"given":"Katsuhide","family":"Fujita","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,2,17]]},"reference":[{"key":"9733_CR1","doi-asserted-by":"publisher","unstructured":"Fatima, S., Kraus, S., & Wooldridge, M. (2014). Principles of Automated Negotiation. Cambridge University Press, Online. https:\/\/doi.org\/10.1017\/CBO9780511751691","DOI":"10.1017\/CBO9780511751691"},{"key":"9733_CR2","doi-asserted-by":"publisher","unstructured":"Sanchez-Anguix, V., Tunal\u00ed, O., Aydo\u01e7an, R., & Julian, V. (2021). Can social agents efficiently perform in automated negotiation? Applied Sciences,11(13). https:\/\/doi.org\/10.3390\/app11136022","DOI":"10.3390\/app11136022"},{"issue":"5","key":"9733_CR3","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1007\/s10458-015-9309-1","volume":"30","author":"T Baarslag","year":"2016","unstructured":"Baarslag, T., Hendrikx, M. J., Hindriks, K. V., & Jonker, C. M. (2016). Learning about the opponent in automated bilateral negotiation: a comprehensive survey of opponent modeling techniques. Autonomous Agents and Multi-Agent Systems, 30(5), 849\u2013898. https:\/\/doi.org\/10.1007\/s10458-015-9309-1","journal-title":"Autonomous Agents and Multi-Agent Systems"},{"key":"9733_CR4","doi-asserted-by":"publisher","unstructured":"Galen\u00a0Last, N. (2012). In: T. Ito, M. Zhang, V. Robu, S. Fatima, & T. Matsuo (Eds.), Agent Smith: opponent model estimation in bilateral multi-issue negotiation (pp. 167\u2013174). Springer, Berlin, Heidelberg . https:\/\/doi.org\/10.1007\/978-3-642-24696-8_12","DOI":"10.1007\/978-3-642-24696-8_12"},{"key":"9733_CR5","doi-asserted-by":"publisher","unstructured":"Krimpen, T., Looije, D., & Hajizadeh, S. (2013). Hardheaded. In: T. Ito, M. Zhang, V. Robu, & T. Matsuo (Eds.), Complex automated negotiations: Theories, models, and software competitions (pp. 223\u2013227). Springer, Berlin, Heidelberg. https:\/\/doi.org\/10.1007\/978-3-642-30737-9_17","DOI":"10.1007\/978-3-642-30737-9_17"},{"key":"9733_CR6","doi-asserted-by":"publisher","unstructured":"Hao, J., & Leung, H. -f. (2014). Cuhkagent: An adaptive negotiation strategy for bilateral negotiations over multiple items. In: I. Marsa-Maestre, M. A. Lopez-Carmona, T. Ito, M. Zhang, Q. Bai, & K. Fujita (Eds.), Novel insights in agent-based complex automated negotiation (pp. 171\u2013179). Springer, Tokyo. https:\/\/doi.org\/10.1007\/978-4-431-54758-7_11","DOI":"10.1007\/978-4-431-54758-7_11"},{"key":"9733_CR7","doi-asserted-by":"publisher","unstructured":"Johnson, E., & Gratch, J. (2021). Comparing the accuracy of frequentist and bayesian models in human-agent negotiation. In: Proceedings of the 21st ACM international conference on intelligent virtual agents. IVA \u201921 (pp. 139\u2013144). Association for Computing Machinery, New York, NY, USA. https:\/\/doi.org\/10.1145\/3472306.3478354","DOI":"10.1145\/3472306.3478354"},{"key":"9733_CR8","doi-asserted-by":"crossref","unstructured":"Hindriks, K., & Tykhonov, D. (2008). Opponent modelling in automated multi-issue negotiation using bayesian learing. In: L. Padgham, D. Parkes, J. Muller, & S. Parsons (Eds.), Proceedings of the 2008 international conference on autonomous agents and multiagent systems (pp. 331\u2013338). Lightning Source UK Ltd., Estoril, Portugal. https:\/\/dl.acm.org\/doi\/10.5555\/1402383.1402433","DOI":"10.65109\/GZVI8746"},{"key":"9733_CR9","doi-asserted-by":"publisher","unstructured":"Williams, C. R., Robu, V., Gerding, E. H., & Jennings, N. R. (2012). Iamhaggler: A negotiation agent for complex environments. In: T. Ito, M. Zhang, V. Robu, S. Fatima, & T. Matsuo (Eds.), New trends in agent-based complex automated negotiations (pp. 151\u2013158). Springer, Berlin, Heidelberg. https:\/\/doi.org\/10.1007\/978-3-642-24696-8_10","DOI":"10.1007\/978-3-642-24696-8_10"},{"key":"9733_CR10","doi-asserted-by":"crossref","unstructured":"Chang, S., & Fujita, K. (2023). A scalable opponent model using bayesian learning for automated bilateral multi-issue negotiation. In: Proceedings of the 2023 international conference on autonomous agents and multiagent systems. AAMAS \u201923 (pp. 2487\u20132489). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC","DOI":"10.65109\/DXFG6607"},{"key":"9733_CR11","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1016\/j.eswa.2019.03.025","volume":"128","author":"F Eshragh","year":"2019","unstructured":"Eshragh, F., Shahbazi, M., & Far, B. (2019). Real-time opponent learning in automated negotiation using recursive bayesian filtering. Expert Systems with Applications, 128, 28\u201353. https:\/\/doi.org\/10.1016\/j.eswa.2019.03.025","journal-title":"Expert Systems with Applications"},{"key":"9733_CR12","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1016\/j.knosys.2015.04.006","volume":"84","author":"J Zhang","year":"2015","unstructured":"Zhang, J., Ren, F., & Zhang, M. (2015). Bayesian-based preference prediction in bilateral multi-issue negotiation between intelligent agents. Knowledge-Based Systems, 84, 108\u2013120. https:\/\/doi.org\/10.1016\/j.knosys.2015.04.006","journal-title":"Knowledge-Based Systems"},{"issue":"5","key":"9733_CR13","doi-asserted-by":"publisher","first-page":"1143","DOI":"10.1007\/s10726-024-09889-7","volume":"33","author":"S Chang","year":"2024","unstructured":"Chang, S., & Fujita, K. (2024). Comb: Scalable concession-driven opponent models using bayesian learning for preference learning in bilateral multi-issue automated negotiation. Group Decision and Negotiation, 33(5), 1143\u20131190. https:\/\/doi.org\/10.1007\/s10726-024-09889-7","journal-title":"Group Decision and Negotiation"},{"key":"9733_CR14","doi-asserted-by":"publisher","unstructured":"Baarslag, T., Hindriks, K., Hendrikx, M., Dirkzwager, A., & Jonker, C. (2014). Decoupling negotiating agents to explore the space of negotiation strategies. In: I. Marsa-Maestre, M. A. Lopez-Carmona, T. Ito, M. Zhang, Q. Bai, & K. Fujita (Eds.), Novel insights in agent-based complex automated negotiation (pp. 61\u201383). Springer, Tokyo. https:\/\/doi.org\/10.1007\/978-4-431-54758-7_4","DOI":"10.1007\/978-4-431-54758-7_4"},{"key":"9733_CR15","doi-asserted-by":"publisher","unstructured":"Baarslag, T., Hindriks, K., Jonker, C., Kraus, S., & Lin, R. (2012). The first automated negotiating agents competition (ANAC2010). In: T. Ito, M. Zhang, V. Robu, S. Fatima, & T. Matsuo (Eds.), New trends in agent-based complex automated negotiations (pp. 113\u2013135). Springer, Berlin, Heidelberg. https:\/\/doi.org\/10.1007\/978-3-642-24696-8_7","DOI":"10.1007\/978-3-642-24696-8_7"},{"key":"9733_CR16","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1016\/j.artint.2012.09.004","volume":"198","author":"T Baarslag","year":"2013","unstructured":"Baarslag, T., Fujita, K., Gerding, E. H., Hindriks, K., Ito, T., Jennings, N. R., Jonker, C., Kraus, S., Lin, R., Robu, V., & Williams, C. R. (2013). Evaluating practical negotiating agents: Results and analysis of the 2011 international competition. Artificial Intelligence, 198, 73\u2013103. https:\/\/doi.org\/10.1016\/j.artint.2012.09.004","journal-title":"Artificial Intelligence"},{"key":"9733_CR17","doi-asserted-by":"publisher","unstructured":"Fujita, K., Ito, T., Baarslag, T., Hindriks, K., Jonker, C., Kraus, S., & Lin, R. (2013). The second automated negotiating agents competition (ANAC2011). In: T. Ito, M. Zhang, V. Robu, & T. Matsuo (Eds.), Complex automated negotiations: theories, models, and software competitions (pp. 183\u2013197). Springer, Berlin, Heidelberg. https:\/\/doi.org\/10.1007\/978-3-642-30737-9_11","DOI":"10.1007\/978-3-642-30737-9_11"},{"key":"9733_CR18","doi-asserted-by":"publisher","unstructured":"Ya\u2019akov\u00a0Gal, K., & Ilany, L. (2015). The fourth automated negotiation competition. In: K. Fujita, T. Ito, M. Zhang, & V. Robu (Eds.), Next frontier in agent-based complex automated negotiation (pp. 129\u2013136). Springer, Tokyo. https:\/\/doi.org\/10.1007\/978-4-431-55525-4_8","DOI":"10.1007\/978-4-431-55525-4_8"},{"key":"9733_CR19","doi-asserted-by":"crossref","unstructured":"Bakker, J., Hammond, A., Bloembergen, D., & Baarslag, T. (2019). Rlboa: A modular reinforcement learning framework for autonomous negotiating agents. In: Proceedings of the 18th international conference on autonomous agents and MultiAgent systems. AAMAS \u201919 (pp. 260\u2013268). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC","DOI":"10.65109\/NHJQ1220"},{"key":"9733_CR20","doi-asserted-by":"crossref","unstructured":"Sengupta, A., Mohammad, Y., & Nakadai, S. (2021). An autonomous negotiating agent framework with reinforcement learning based strategies and adaptive strategy switching mechanism. In: Proceedings of the 20th international conference on autonomous agents and MultiAgent systems. AAMAS\u201921 (pp. 1163\u20131172). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC","DOI":"10.65109\/VYGB4348"},{"key":"9733_CR21","doi-asserted-by":"crossref","unstructured":"Chen, S., Sun, Q., You, H., Yang, T., & Hao, J. (2023). Transfer learning based agent for automated negotiation. In: Proceedings of the 2023 international conference on autonomous agents and multiagent systems. AAMAS \u201923 (pp. 2895\u20132898). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC","DOI":"10.65109\/VLWF1223"},{"key":"9733_CR22","doi-asserted-by":"publisher","unstructured":"Chen, S., Yang, T., You, H., Zhao, J., Hao, J., & Weiss, G. (2023). Transfer reinforcement learning based negotiating agent framework. In: Advances in Knowledge Discovery and Data Mining: 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25\u201328, 2023, Proceedings, Part II (pp. 386\u2013397). Springer, Berlin, Heidelberg. https:\/\/doi.org\/10.1007\/978-3-031-33377-4_30","DOI":"10.1007\/978-3-031-33377-4_30"},{"key":"9733_CR23","doi-asserted-by":"publisher","unstructured":"Wu, L., Chen, S., Gao, X., Zheng, Y., & Hao, J. (2021). Detecting and learning against unknown opponents for automated negotiations. In: D. N. Pham, T. Theeramunkong, G. Governatori, & F. Liu (Eds.), PRICAI 2021: Trends in artificial intelligence (pp. 17\u201331). Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-030-89370-5_2","DOI":"10.1007\/978-3-030-89370-5_2"},{"key":"9733_CR24","unstructured":"Chen, S., Zhao, J., Weiss, G., Su, R., & Lei, K. (2023). An effective negotiating agent framework based on deep offline reinforcement learning. In: R. J. Evans, & I. Shpitser (Eds.), Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence. Proceedings of Machine Learning Research (vol. 216, pp. 324\u2013335). PMLR, Pittsburgh, PA, USA. https:\/\/proceedings.mlr.press\/v216\/chen23c.html"},{"key":"9733_CR25","doi-asserted-by":"publisher","unstructured":"Aydo\u011fan, R., Baarslag, T., Fujita, K., Hoos, H.H., Jonker, C.M., Mohammad, Y., & Renting, B.M. (2023). The 13th international automated negotiating agent competition challenges and results. In: R. Hadfi, R. Aydo\u011fan, T. Ito,& R. Arisaka (Eds.), Recent advances in agent-based negotiation: applications and competition challenges (pp. 87\u2013101). Springer, Singapore. https:\/\/doi.org\/10.1007\/978-981-99-0561-4_5","DOI":"10.1007\/978-981-99-0561-4_5"},{"key":"9733_CR26","doi-asserted-by":"publisher","unstructured":"Aydo\u011fan, R., Baarslag, T., Fujita, K., Mell, J., Gratch, J., Jonge, D., Mohammad, Y., Nakadai, S., Morinaga, S., Osawa, H., Aranha, C., & Jonker, C. M. (2020). Challenges and main results of the automated negotiating agents competition (ANAC) 2019. In: N. Bassiliades, G. Chalkiadakis, & D. Jonge (Eds.), Multi-agent systems and agreement technologies (pp. 366\u2013381). Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-030-66412-1_23","DOI":"10.1007\/978-3-030-66412-1_23"},{"key":"9733_CR27","doi-asserted-by":"publisher","unstructured":"Chang, S., & Fujita, K. (2023). A fine-tuning aggregation convolutional neural network surrogate model of strategy selecting mechanism for repeated-encounter bilateral automated negotiation. In: Proceedings of the 15th international conference on agents and artificial intelligence - volume 2: ICAART (pp. 277\u2013288). SciTePress, Lisbon, Portugal. https:\/\/doi.org\/10.5220\/0011701300003393","DOI":"10.5220\/0011701300003393"},{"key":"9733_CR28","doi-asserted-by":"crossref","unstructured":"Renting, B. M., Hoos, H. H., & Jonker, C. M. (2020). Automated configuration of negotiation strategies. In: Proceedings of the 19th international conference on autonomous agents and multiagent systems. AAMAS\u201920 (pp. 1116\u20131124). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC","DOI":"10.65109\/ANWE5163"},{"key":"9733_CR29","doi-asserted-by":"crossref","unstructured":"Renting, B. M., Hoos, H. H., & Jonker, C. M. (2022). Automated configuration and usage of strategy portfolios for mixed-motive bargaining. In: Proceedings of the 21st international conference on autonomous agents and multiagent systems. AAMAS\u201922 (pp. 1101\u20131109). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC","DOI":"10.65109\/AQIR4400"},{"key":"9733_CR30","doi-asserted-by":"publisher","unstructured":"Ikrashi, M., & Fujita, K. (2014). Compromising strategy using weighted counting in multi-times negotiations. In: 2014 IIAI 3rd International conference on advanced applied informatics (pp. 453\u2013458). https:\/\/doi.org\/10.1109\/IIAI-AAI.2014.97","DOI":"10.1109\/IIAI-AAI.2014.97"},{"issue":"1","key":"9733_CR31","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1111\/j.1467-8640.2012.00463.x","volume":"30","author":"R Lin","year":"2014","unstructured":"Lin, R., Kraus, S., Baarslag, T., Tykhonov, D., Hindriks, K., & Jonker, C. M. (2014). Genius: An integrated environment for supporting the design of generic automated negotiators. Computational Intelligence, 30(1), 48\u201370. https:\/\/doi.org\/10.1111\/j.1467-8640.2012.00463.x","journal-title":"Computational Intelligence"},{"key":"9733_CR32","doi-asserted-by":"publisher","unstructured":"Baarslag, T., Hendrikx, M., Hindriks, K., & Jonker, C. (2013). Predicting the performance of opponent models in automated negotiation. In: 2013 IEEE\/WIC\/ACM International joint conferences on web intelligence (WI) and intelligent agent technologies (IAT) (vol. 2, pp. 59\u201366). IEEE, United States. https:\/\/doi.org\/10.1109\/WI-IAT.2013.91","DOI":"10.1109\/WI-IAT.2013.91"},{"key":"9733_CR33","doi-asserted-by":"publisher","unstructured":"Tunal\u0131, O., Aydo\u011fan, R., & Sanchez-Anguix, V. (2017). Rethinking frequency opponent modeling in automated negotiation. In: PRIMA 2017: Principles and practice of multi-agent systems (pp. 263\u2013279). Springer, Nice, France. https:\/\/doi.org\/10.1007\/978-3-319-69131-2_16","DOI":"10.1007\/978-3-319-69131-2_16"},{"key":"9733_CR34","doi-asserted-by":"publisher","unstructured":"Hosokawa, Y., & Fujita, K. (2020). Opponent\u2019s preference estimation considering their offer transition in multi-issue closed negotiations. IEICE Transactions on Information and Systems,E103.D(12), 2531\u20132539. https:\/\/doi.org\/10.1587\/transinf.2020sap0001","DOI":"10.1587\/transinf.2020sap0001"},{"key":"9733_CR35","doi-asserted-by":"publisher","unstructured":"Baarslag, T. (2016). Measuring the Performance of Online Opponent Models (pp. 111\u2013127). Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-319-28243-5_6","DOI":"10.1007\/978-3-319-28243-5_6"},{"key":"9733_CR36","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1016\/j.artint.2016.04.001","volume":"237","author":"F Zafari","year":"2016","unstructured":"Zafari, F., & Nassiri-Mofakham, F. (2016). Popponent: Highly accurate, individually and socially efficient opponent preference model in bilateral multi issue negotiations. Artificial Intelligence, 237, 59\u201391. https:\/\/doi.org\/10.1016\/j.artint.2016.04.001","journal-title":"Artificial Intelligence"},{"issue":"24","key":"9733_CR37","doi-asserted-by":"publisher","first-page":"29741","DOI":"10.1007\/s10489-023-05001-9","volume":"53","author":"MO Keskin","year":"2023","unstructured":"Keskin, M. O., Buzcu, B., & Aydo\u011fan, R. (2023). Conflict-based negotiation strategy for human-agent negotiation. Applied Intelligence, 53(24), 29741\u201329757. https:\/\/doi.org\/10.1007\/s10489-023-05001-9","journal-title":"Applied Intelligence"},{"key":"9733_CR38","doi-asserted-by":"publisher","unstructured":"Sim, K. M., Guo, Y., & Shi, B. (2009). Blgan: Bayesian learning and genetic algorithm for supporting negotiation with incomplete information. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics),39(1), 198\u2013211. https:\/\/doi.org\/10.1109\/TSMCB.2008.2004501","DOI":"10.1109\/TSMCB.2008.2004501"},{"key":"9733_CR39","doi-asserted-by":"publisher","unstructured":"Niemann, C., & Lang, F. (2009). In: T. Ito, M. Zhang, V. Robu, S. Fatima, & T. Matsuo (Eds.), Assess your opponent: A bayesian process for preference observation in multi-attribute negotiations (pp. 119\u2013137). Springer, Berlin, Heidelberg. https:\/\/doi.org\/10.1007\/978-3-642-03190-8_6","DOI":"10.1007\/978-3-642-03190-8_6"},{"issue":"1","key":"9733_CR40","doi-asserted-by":"publisher","first-page":"22","DOI":"10.22201\/icat.16656423.2018.16.1.699","volume":"16","author":"U Kiruthika","year":"2019","unstructured":"Kiruthika, U., & Somasundaram, T. S. (2019). Efficient agent-based negotiation by predicting opponent preferences using ahp. Journal of Applied Research and Technology, 16(1), 22\u201334. https:\/\/doi.org\/10.22201\/icat.16656423.2018.16.1.699","journal-title":"Journal of Applied Research and Technology"},{"key":"9733_CR41","doi-asserted-by":"publisher","unstructured":"Coehoorn, R. M., & Jennings, N. R. (2004). Learning on opponent\u2019s preferences to make effective multi-issue negotiation trade-offs. In: Proceedings of the 6th international conference on electronic commerce. ICEC \u201904 (pp. 59\u201368). Association for Computing Machinery, New York, NY, USA. https:\/\/doi.org\/10.1145\/1052220.1052229","DOI":"10.1145\/1052220.1052229"},{"key":"9733_CR42","volume-title":"Rules of Encounter: Designing Conventions for Automated Negotiation Among Computers","author":"JS Rosenschein","year":"1994","unstructured":"Rosenschein, J. S., & Zlotkin, G. (1994). Rules of Encounter: Designing Conventions for Automated Negotiation Among Computers. Cambridge, MA, USA: MIT Press."},{"key":"9733_CR43","doi-asserted-by":"publisher","unstructured":"Kloek, T., & Dijk, H. K. (1978). Bayesian estimates of equation system parameters: An application of integration by monte carlo. Econometrica,46(1), 1\u201319. https:\/\/doi.org\/10.2307\/1913641. Accessed 29 Jan 2024","DOI":"10.2307\/1913641"},{"key":"9733_CR44","doi-asserted-by":"publisher","unstructured":"Mohammad, Y., Nakadai, S., & Greenwald, A. (2020). Negmas: A platform for automated negotiations. In: PRIMA 2020: Principles and Practice of Multi-Agent Systems: 23rd International Conference, Nagoya, Japan, November 18\u201320, 2020, Proceedings (pp. 343\u2013351). Springer, Berlin, Heidelberg. https:\/\/doi.org\/10.1007\/978-3-030-69322-0_23","DOI":"10.1007\/978-3-030-69322-0_23"},{"key":"9733_CR45","unstructured":"Williams, C. R., Robu, V., Gerding, E. H., & Jennings, N. R. (2011). Using gaussian processes to optimise concession in complex negotiations against unknown opponents. In: Proceedings of the twenty-second international joint conference on artificial intelligence - volume volume one. IJCAI\u201911 (pp. 432\u2013438). AAAI Press, Barcelona, Catalonia, Spain"},{"key":"9733_CR46","doi-asserted-by":"publisher","unstructured":"Chen, S., & Weiss, G. (2014). In: I. Marsa-Maestre, M. A. Lopez-Carmona, T. Ito, M. Zhang, Q. Bai, & K. Fujita (Eds.), OMAC: A discrete wavelet transformation based negotiation agent (pp. 187\u2013196). Springer, Tokyo. https:\/\/doi.org\/10.1007\/978-4-431-54758-7_13","DOI":"10.1007\/978-4-431-54758-7_13"},{"key":"9733_CR47","doi-asserted-by":"publisher","unstructured":"Koeman, V. J., Boon, K., Oever, J. Z., Dumitru-Guzu, M., & Stanculescu, L. C. (2015). In: K. Fujita, T. Ito, M. Zhang, & V. Robu (Eds.), The fawkes agent\u2014the ANAC 2013 negotiation contest winner (pp. 143\u2013151). Springer, Tokyo. https:\/\/doi.org\/10.1007\/978-4-431-55525-4_10","DOI":"10.1007\/978-4-431-55525-4_10"},{"key":"9733_CR48","doi-asserted-by":"publisher","unstructured":"Erez, E. S., I.Z., & Hermel, D. (2017). Automatic negotiation: playing the domain instead of the opponent. Journal of Experimental & Theoretical Artificial Intelligence,29(3), 597\u2013616. https:\/\/doi.org\/10.1080\/0952813X.2016.1212102","DOI":"10.1080\/0952813X.2016.1212102"},{"issue":"4","key":"9733_CR49","doi-asserted-by":"publisher","first-page":"697","DOI":"10.1007\/s10458-015-9302-8","volume":"30","author":"L Ilany","year":"2016","unstructured":"Ilany, L., & Gal, Y. (2016). Algorithm selection in bilateral negotiation. Autonomous Agents and Multi-Agent Systems, 30(4), 697\u2013723. https:\/\/doi.org\/10.1007\/s10458-015-9302-8","journal-title":"Autonomous Agents and Multi-Agent Systems"},{"key":"9733_CR50","doi-asserted-by":"publisher","unstructured":"Kakimoto, S., & Fujita, K. (2017). In: K. Fujita, Q. Bai, T. Ito, M. Zhang, F. Ren, R. Aydo\u011fan, & R. Hadfi (Eds.), RandomDance: compromising strategy considering interdependencies of issues with randomness (pp. 185\u2013189). Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-319-51563-2_13","DOI":"10.1007\/978-3-319-51563-2_13"},{"key":"9733_CR51","doi-asserted-by":"publisher","unstructured":"De\u00a0Jonge, D. (2022). An analysis of the linear bilateral anac domains using the micro benchmark strategy. In: Raedt, L. D. (Ed.), Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, IJCAI-22 (pp. 223\u2013229). International Joint Conferences on Artificial Intelligence Organization, Messe Wien, Vienna, Austria. https:\/\/doi.org\/10.24963\/ijcai.2022\/32","DOI":"10.24963\/ijcai.2022\/32"}],"container-title":["Autonomous Agents and Multi-Agent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10458-026-09733-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10458-026-09733-z","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10458-026-09733-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T15:47:10Z","timestamp":1771343230000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10458-026-09733-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,17]]},"references-count":51,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,6]]}},"alternative-id":["9733"],"URL":"https:\/\/doi.org\/10.1007\/s10458-026-09733-z","relation":{},"ISSN":["1387-2532","1573-7454"],"issn-type":[{"value":"1387-2532","type":"print"},{"value":"1573-7454","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,17]]},"assertion":[{"value":"28 February 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 January 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 February 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of Interest"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"8"}}