Studying the Impact of Negotiation Environments on Negotiation Teams' Performance

[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.2012.07.017S174021

Teaching game theory and rationality to artificial intelligence master's students

[EN] Game theory is a branch of applied mathematics used in economics and artificial intelligence to study the behaviour of self-interested agents. In game theory, agents are rational, which means that they will always analyse the situation intelligently and seek their own benefit. The concept of rationality in game theory and artificial intelligence is based on the rigorous analysis of a conflict between self-interested agents in which they exclusively seek to maximise their utility in the defined terms of the game. Are we humans totally rational in making our decisions? Do we consider all the possible options to get the maximum benefit or do we let ourselves be influenced by other factors such as feelings? In this paper, we present the methods used with students of the Master's Degree in Artificial Intelligence at the Universitat Politècnica de València to teach game theory and rationality. In order to ensure that the students were able to assimilate the concepts of game theory, the classic master class method has been combined with new technologies to make the lesson dynamic. In this way, the explanation of theoretical concepts has been mixed with small games carried out with the students, always guided by the professor, using tools such as Kahoot and Socrative. The experience acquired during the lessons shows that even in the case of students coming from engineering backgrounds with a solid mathematical base, in general, they still lack this abstract understanding of rationality and act according to their feelings in many cases. This invites reflection and attempts to provide students with guidance for the correct understanding of the concept of rationality along with other complex concepts typical of game theory. On the other hand, we also show the results obtained from a series of games played in the classroom that demonstrate this lack of rationality in the students, what obviously makes them human. This can be interpreted as the fact that the utility functions of the agents that represent humans in a game do not capture all the variables, such as feelings, that a person takes into account when making certain types of decisions. The evaluation of the knowledge acquired by the students was done through an open project that consisted in designing a game including the rules of the game, applicable concepts of equilibrium, and analysis of the rationality of the players. This allowed the assessment of the knowledge acquired by the students during the lessons carried out with the dynamic methodology obtaining very satisfactory results. In this sense, the academic results of the students regarding the average grades obtained were higher than in previous courses in which this methodology was not applied. On the other hand, student satisfaction was also high, as shown by the surveys carried out.This work was partially supported by MINECO/FEDER RTI2018-095390-B-C31 project of the Spanish government.Jordán, J.; Julian Inglada, VJ. (2021). Teaching game theory and rationality to artificial intelligence master's students. IATED. 3852-3858. https://doi.org/10.21125/inted.2021.0792S3852385

Cinema, popular entertainment, literature and television

This is an attempt to analyze the relationship between spanish cinema and the popular culture and entertainment through its history

Case-Based Argumentation Framework. Dialogue Protocol

On top of the simpler ability to interact, open MAS must include mechanisms for their agents to reach agreements by taking into account their social context. Argumentation provides MAS with a framework that assures a rational communication, which allows agents to reach agreements when conflicts of opinion arise. In this report we present the communication protocol that agents of a case-based argumentation framework use to interact when they engage in argumentation dialogues. The syntax and semantics of the framework are formalised and discussed.Heras Barberá, SM.; Botti Navarro, VJ.; Julian Inglada, VJ. (2011). Case-Based Argumentation Framework. Dialogue Protocol. http://hdl.handle.net/10251/1109

A Computational Argumentation Framework for Agent Societies

Starting from the idea that the social context of agents determines the way in which agents can argue and reach agreements, this context should have a decisive influence in the computational representation of arguments. In this report, we advance research in the area of computational frameworks for agent argumentation by proposing a new argumentation framework (AF) for the design of open MAS in which the participating software agents are able to manage and exchange arguments between themselves taking into account the agents¿ social context. In order to do this, we have analysed the necessary requirements for this type of framework 1 and taken into account them in the design of our framework. Also, the knowledge resources that the agents can use to manage arguments in this framework are presented in this work. In addition, if heterogeneous agents can interact in the framework, they need a common language to represent arguments and argumentation processes. To cope with this, we have also designed an argumentation ontology to represent arguments and argumentation concepts in our framework.Heras Barberá, SM.; Botti Navarro, VJ.; Julian Inglada, VJ. (2011). A Computational Argumentation Framework for Agent Societies. http://hdl.handle.net/10251/1103

Case-Based Argumentation Framework. Reasoning Process

The capability of reaching agreements is a necessary feature that large computer systems where agents interoperate must include. In these systems, agents represent self-motivated entities that have a social context, including dependency relations among them, and different preferences and beliefs. Without agreement there is no cooperation and thus, complex tasks which require the interaction of agents with different points of view cannot be performed. In this work, we follow a case-based argumentation approach for the design and implementation of Multi-Agent Systems where agents reach agreements by arguing and improve their argumentation skills from experience. A set of knowledge resources and a reasoning process that agents can use to manage their positions and arguments are presented.Heras Barberá, SM.; Botti Navarro, VJ.; Julian Inglada, VJ. (2011). Case-Based Argumentation Framework. Reasoning Process. http://hdl.handle.net/10251/1109

Case-Based Argumentation Framework. Strategies

In agent societies, agents perform complex tasks that require different levels of intelligence and give rise to interactions among them. From these interactions, conflicts of opinion can arise, specially when MAS become adaptive and open with heterogeneous agents dynamically entering in or leaving the system. Therefore, software agents willing to participate in this type of systems will require to include extra capabilities to explicitly represent and generate agreements on top of the simpler ability to interact. In addition, agents can take advantage of previous argumentation experiences to follow dialogue strategies and easily persuade other agents to accept their opinions. Our insight is that CBR can be very useful to manage argumentation in open MAS and devise argumentation strategies based on previous argumentation experiences. To demonstrate the foundations of this suggestion, this report presents the work that we have done to develop case-based argumentation strategies in agent societies. Thus, we propose a case-based argumentation framework for agent societies and define heuristic dialogue strategies based on it. The framework has been implemented and evaluated in a real customer support application.Heras Barberá, SM.; Botti Navarro, VJ.; Julian Inglada, VJ. (2011). Case-Based Argumentation Framework. Strategies. http://hdl.handle.net/10251/1109

Applying CBR to manage argumentation in MAS

[EN] The application of argumentation theories and techniques in multi-agent systems has become a prolific area of research. Argumentation allows agents to harmonise two types of disagreement situations: internal, when the acquisition of new information (e.g., about the environment or about other agents) produces incoherences in the agents' mental state; and external, when agents that have different positions about a topic engage in a discussion. The focus of this paper is on the latter type of disagreement situations. In those settings, agents must be able to generate, select and send arguments to other agents that will evaluate them in their turn. An efficient way for agents to manage these argumentation abilities is by using case-based reasoning, which has been successfully applied to argumentation from its earliest beginnings. This reasoning methodology also allows agents to learn from their experiences and therefore, to improve their argumentation skills. This paper analyses the advantages of applying case-based reasoning to manage arguments in multi-agent systems dialogues, identifies open issues and proposes new ideas to tackle them.This work was partially supported by CONSOLIDERINGENIO 2010 under grant CSD2007-00022 and by the Spanish government and FEDER funds under CICYT TIN2005-03395 and TIN2006-14630-C0301 projects.Heras Barberá, SM.; Julian Inglada, VJ.; Botti Navarro, VJ. (2010). Applying CBR to manage argumentation in MAS. International Journal of Reasoning-based Intelligent Systems. 2(2):110-117. https://doi.org/10.1504/IJRIS.2010.034906S1101172

Modelling dialogues in agent societies

Besides the simpler ability to interact, open multi-agent systems must include mechanisms for their agents to reach agreements by taking into account their social context. Argumentation provides multi-agent systems with a framework that assures a rational communication, which allows agents to reach agreements when conflicts of opinion arise. In this paper, we present the dialogue protocol that agents of a case-based argumentation framework can use to interact when they engage in argumentation dialogues. The syntax and semantics of the argumentation protocol are formalised and discussed. To illustrate our proposal, we have applied the protocol in the context of a water market. By using our dialogue protocol, agents represent water users that are able to explore different water allocations and justify their views about what is the best water distribution in a certain environment.This work is supported by the Spanish government Grants CONSOLIDER INGENIO 2010 CSD2007-00022, MINECO/FEDER TIN2012-36586-C03-01, and MICINN TIN2011-27652-C03-01.Heras Barberá, SM.; Botti Navarro, VJ.; Julian Inglada, VJ. (2014). Modelling dialogues in agent societies. Engineering Applications of Artificial Intelligence. 34:208-226. https://doi.org/10.1016/j.engappai.2014.06.003S2082263