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[EN] In the last few years, we witnessed a growing body of literature about automated negotiation. Mainly, negotiating agents are either purely self-driven by maximizing their utility function or by assuming a cooperative stance by all parties involved in the negotiation. We argue that, while optimizing one's utility function is essential, agents in a society should not ignore the opponent's utility in the final agreement to improve the agent's long-term perspectives in the system. This article aims to show whether it is possible to design a social agent (i.e., one that aims to optimize both sides' utility functions) while performing efficiently in an agent society. Accordingly, we propose a social agent supported by a portfolio of strategies, a novel tit-for-tat concession mechanism, and a frequency-based opponent modeling mechanism capable of adapting its behavior according to the opponent's behavior and the state of the negotiation. The results show that the proposed social agent not only maximizes social metrics such as the distance to the Nash bargaining point or the Kalai point but also is shown to be a pure and mixed equilibrium strategy in some realistic agent societies. ; This work was partially supported by the MINECO/FEDER RTI2018-095390-B-C31 project of the Spanish government and partially supported by a grant of The Scientific and Research Council of Turkey (TUBITAK) with grant number 118E197. The contents of this article reflect the ideas and positions of the authors and do not necessarily reflect the ideas or positions of TUBITAK. ; Sanchez-Anguix, V.; Tunali, O.; Aydogan, R.; Julian, V. (2021). Can Social Agents Efficiently Perform in Automated Negotiation?. Applied Sciences. 11(13):1-26. https://doi.org/10.3390/app11136022 ; S ; 1 ; 26 ; 11 ; 13

[EN] In this article we study the impact of the negotiation environment on the performance of several intra-team strategies (team dynamics) for agent-based negotiation teams that negotiate with an opponent. An agent-based negotiation team is a group of agents that joins together as a party because they share common interests in the negotiation at hand. It is experimentally shown how negotiation environment conditions like the deadline of both parties, the concession speed of the opponent, similarity among team members, and team size affect performance metrics like the minimum utility of team members, the average utility of team members, and the number of negotiation rounds. Our goal is identifying which intra-team strategies work better in different environmental conditions in order to provide useful knowledge for team members to select appropriate intra-team strategies according to environmental conditions. ; This work is supported by TIN2011-27652-C03-01, TIN2009-13839-C03-01, CSD2007-00022 of the Spanish Government, and FPU Grant AP2008-00600 awarded to Victor Sanchez-Anguix. We would also like to thank anonymous reviewers and assistants of AAMAS 2011 who helped us to improve our previous work, making this present work possible. ; Sanchez-Anguix, V.; Julian Inglada, VJ.; Botti, V.; García-Fornes, A. (2013). Studying the impact of negotiation environments on negotiation teams' performance. Information Sciences. 219:17-40. https://doi.org/10.1016/j.ins.2012.07.017 ; S ; 17 ; 40 ; 219

[EN] In this article, an agent-based negotiation model for negotiation teams that negotiate a deal with an opponent is presented. Agent-based negotiation teams are groups of agents that join together as a single negotiation party because they share an interest that is related to the negotiation process. The model relies on a trusted mediator that coordinates and helps team members in the decisions that they have to take during the negotiation process: which offer is sent to the opponent, and whether the offers received from the opponent are accepted. The main strength of the proposed negotiation model is the fact that it guarantees unanimity within team decisions since decisions report a utility to team members that is greater than or equal to their aspiration levels at each negotiation round. This work analyzes how unanimous decisions are taken within the team and the robustness of the model against different types of manipulations. An empirical evaluation is also performed to study the impact of the different parameters of the model. ; This work is supported by TIN2008-04446, PROMETEO/2008/051, TIN2009-13839-C03-01, CSD2007-00022 of the Spanish government, and FPU Grant AP2008-00600 awarded to Victor Sanchez-Anguix. This paper was recommended by Associate Editor X. Wang. ; Sanchez-Anguix, V.; Julian Inglada, VJ.; Botti, V.; García-Fornes, A. (2012). Reaching unanimous agreements within agent-based negotiation teams with linear and monotonic utility functions. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics. 42(3):778-792. https://doi.org/10.1109/TSMCB.2011.2177658 ; S ; 778 ; 792 ; 42 ; 3

[EN] Nowadays, there is increasing interest in the development of teamwork skills in the educational context. This growing interest is motivated by its pedagogical effectiveness and the fact that, in labour contexts, enterprises organise their employees in teams to carry out complex projects. Despite its crucial importance in the classroom and industry, there is a lack of support for the team formation process. Not only do many factors influence team performance, but the problem becomes exponentially costly if teams are to be optimised. In this article, we propose a tool whose aim it is to cover such a gap. It combines artificial intelligence techniques such as coalition structure generation, Bayesian learning, and Belbin s role theory to facilitate the generation of working groups in an educational context. This tool improves current state of the art proposals in three ways: i) it takes into account the feedback of other teammates in order to establish the most predominant role of a student instead of self-perception questionnaires; ii) it handles uncertainty with regard to each student s predominant team role; iii) it is iterative since it considers information from several interactions in order to improve the estimation of role assignments. We tested the performance of the proposed tool in an experiment involving students that took part in three different team activities. The experiments suggest that the proposed tool is able to improve different teamwork aspects such as team dynamics and student satisfaction. ; This work is supported by the following projects: TIN2014-55206-R, TIN2012-36586-C03-01, PROMETEOII/2013/019, TIN2015-65515-C4-1-R, H2020-ICT-2015-688095. ; Alberola Oltra, JM.; Del Val Noguera, E.; Sanchez-Anguix, V.; Palomares Chust, A.; Teruel Serrano, MD. (2016). An artificial intelligence tool for heterogeneous team formation in the classroom. Knowledge-Based Systems. 101:1-14. https://doi.org/10.1016/j.knosys.2016.02.010 ; S ; 1 ; 14 ; 101

Ambient Intelligence aims to offer personalized services and easier ways of interaction between people and systems. Since several users and systems may coexist in these environments, it is quite possible that entities with opposing preferences need to cooperate to reach their respective goals. Automated negotiation is pointed as one of the mechanisms that may provide a solution to this kind of problems. In this article, a multi-issue bilateral bargaining model for Ambient Intelligence domains is presented where it is assumed that agents have computational bounded resources and do not know their opponents' preferences. The main goal of this work is to provide negotiation models that obtain efficient agreements while maintaining the computational cost low. A niching genetic algorithm is used before the negotiation process to sample one's own utility function (self-sampling). During the negotiation process, genetic operators are applied over the opponent's and one's own offers in order to sample new offers that are interesting for both parties. Results show that the proposed model is capable of outperforming similarity heuristics which only sample before the negotiation process and of obtaining similar results to similarity heuristics which have access to all of the possible offers. (C) 2010 Elsevier Inc. All rights reserved. ; This work is supported by TIN2008-04446, PROMETEO/2008/051, TIN2009-13839-C03-01, CSD2007-00022 of the Spanish government, and FPU Grant AP2008-00600 awarded to V.Sanchez-Anguix. ; Sanchez-Anguix, V.; Valero Cubas, S.; Julian Inglada, VJ.; Botti Navarro, VJ.; García Fornes, AM. (2013). Evolutionary-aided negotiation model for bilateral bargaining in Ambient Intelligence domains with complex utility functions. Information Sciences. 222:25-46. https://doi.org/10.1016/j.ins.2010.11.018 ; S ; 25 ; 46 ; 222

[EN] This work proposes a persuasion model based on argumentation theory and users' characteristics for improving the use of resources in bike sharing systems, fostering the use of the bicycles and thus contributing to greater energy sustainability by reducing the use of carbon-based fuels. More specifically, it aims to achieve a balanced network of pick-up and drop-off stations in urban areas with the help of the users, thus reducing the dedicated management trucks that redistribute bikes among stations. The proposal aims to persuade users to choose different routes from the shortest route between a start and an end location. This persuasion is carried out when it is not possible to park the bike in the desired station due to the lack of parking slots, or when the user is highly influenceable. Differently to other works, instead of employing a single criteria to recommend alternative stations, the proposed system can incorporate a variety of criteria. This result is achieved by providing a defeasible logic-based persuasion engine that is capable of aggregating the results from multiple recommendation rules. The proposed framework is showcased with an example scenario of a bike sharing system. ; This work was supported by the projects TIN2015-65515-C4-1-R and TIN2017-89156-R of the Spanish government, and by the grant program for the recruitment of doctors for the Spanish system of science and technology (PAID-10-14) of the Universitat Politècnica de València. ; Diez-Alba, C.; Palanca Cámara, J.; Sanchez-Anguix, V.; Heras, S.; Giret Boggino, AS.; Julian Inglada, VJ. (2019). Towards a Persuasive Recommender for Bike Sharing Systems: A Defeasible Argumentation Approach. Energies. 12(4):1-19. https://doi.org/10.3390/en12040662 ; S ; 1 ; 19 ; 12 ; 4 ; Erdoğan, G., Laporte, G., & Wolfler Calvo, R. (2014). The static bicycle relocation problem with demand intervals. European Journal of Operational Research, 238(2), 451-457. doi:10.1016/j.ejor.2014.04.013 ; Alvarez-Valdes, R., Belenguer, J. M., Benavent, E., ...