A finer grained modeling of rational coalitions using goals

We propose an extension of Coalitional ATL (a logic for reasoning about coalitions and their formation process, see [10]) by goals. This goal framework allows for a finer grained modeling of coalitions: Coalitional frameworks, based on Dungs’s abstract argumentation framework, are used to point out conflicts between agents, and goals refer to agents’ subjective incentives to join (or not to join) coalitions. We focus on two different aspects for cooperation allowing a more practical modeling of systemsWorkshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

A finer grained modeling of rational coalitions using goals

We propose an extension of Coalitional ATL (a logic for reasoning about coalitions and their formation process, see [10]) by goals. This goal framework allows for a finer grained modeling of coalitions: Coalitional frameworks, based on Dungs’s abstract argumentation framework, are used to point out conflicts between agents, and goals refer to agents’ subjective incentives to join (or not to join) coalitions. We focus on two different aspects for cooperation allowing a more practical modeling of systemsWorkshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

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

Argue to agree: A case-based argumentation approach

[EN] 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 propose a case-based argumentation approach for 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. These elements are implemented and validated in a customer support application.This work is supported by the Spanish government grants [CONSOLIDER-INGENIO 2010 CSD2007-00022, TIN2008-04446, and TIN2009-13839-C03-01] and by the GVA project [PROMETEO 2008/051].Heras Barberá, SM.; Jordán Prunera, JM.; Botti, V.; Julian Inglada, VJ. (2013). Argue to agree: A case-based argumentation approach. International Journal of Approximate Reasoning. 54(1):82-108. https://doi.org/10.1016/j.ijar.2012.06.005S8210854

Resilience, reliability, and coordination in autonomous multi-agent systems

Acknowledgements The research reported in this paper was funded and supported by various grants over the years: Robotics and AI in Nuclear (RAIN) Hub (EP/R026084/1); Future AI and Robotics for Space (FAIR-SPACE) Hub (EP/R026092/1); Offshore Robotics for Certification of Assets (ORCA) Hub (EP/R026173/1); the Royal Academy of Engineering under the Chair in Emerging Technologies scheme; Trustworthy Autonomous Systems “Verifiability Node” (EP/V026801); Scrutable Autonomous Systems (EP/J012084/1); Supporting Security Policy with Effective Digital Intervention (EP/P011829/1); The International Technology Alliance in Network and Information Sciences.Peer reviewedPostprin

An Ontological-based Knowledge-Representation Formalism for Case-Based Argumentation

The final publication is available at Springer via http://dx.doi.org/10.1007/s10796-014-9524-3[EN] In open multi-agent systems, agents can enter or leave the system, interact, form societies, and have dependency relations with each other. In these systems, when agents have to collaborate or coordinate their activities to achieve their objectives, their different interests and preferences can come into conflict. Argumentation is a powerful technique to harmonise these conflicts. However, in many situations the social context of agents determines the way in which agents can argue to reach agreements. In this paper, we advance research in the computational representation of argumentation frameworks by proposing a new ontologicalbased, knowledge-representation formalism for the design of open MAS in which the participating software agents are able to manage and exchange arguments with each other taking into account the agents’ social context. This formalism is the core of a case-based argumentation framework for agent societies. In addition, we present an example of the performance of the formalism in a real domain that manages the requests received by the technicians of a call centre.This work is supported by the Spanish government grants [CONSOLIDER-INGENIO 2010 CSD2007-00022, TIN2011-27652-C03-01, and TIN2012-36586-C03-01] and by the GVA project [PROMETEO II/2013/019].Heras Barberá, SM.; Botti, V.; Julian Inglada, VJ. (2014). An Ontological-based Knowledge-Representation Formalism for Case-Based Argumentation. Information Systems Frontiers. 1-20. https://doi.org/10.1007/s10796-014-9524-3S120Amgoud, L. (2005). An argumentation-based model for reasoning about coalition structures. In 2nd international workshop on argumentation in multi-agent systems, argmas-05(pp. 1–12). Springer.Amgoud, L., Dimopolous, Y., Moraitis, P. (2007). A unified and general framework for argumentation-based negotiation. In 6th international joint conference on autonomous agents and multiagent systems, AAMAS-07. IFAAMAS.Atkinson, K., & Bench-Capon, T. (2008). Abstract argumentation scheme frameworks. In Proceedings of the 13th international conference on artificial intelligence: methodology, systems and applications, AIMSA-08, lecture notes in artificial intelligence (Vol. 5253, pp. 220–234). Springer.Aulinas, M., Tolchinsky, P., Turon, C., Poch, M., Cortés, U. (2012). Argumentation-based framework for industrial wastewater discharges management. Engineering Applications of Artificial Intelligence, 25(2), 317–325.Bench-Capon, T., & Atkinson, K. (2009). Argumentation in artificial intelligence, chap. abstract argumentation and values (pp. 45–64). Springer.Bench-Capon, T., & Sartor, G. (2003). A model of legal reasoning with cases incorporating theories and values. Artificial Intelligence, 150(1-2), 97–143.Bulling, N., Dix, J., Chesñevar, C.I. (2008). Modelling coalitions: ATL + argumentation. In Proceedings of the 7th international joint conference on autonomous agents and multiagent systems, AAMAS-08 (Vol. 2, pp. 681–688). ACM Press.Chesñevar, C., McGinnis, J., Modgil, S., Rahwan, I., Reed, C., Simari, G., South, M., Vreeswijk, G., Willmott, S. (2006). Towards an argument interchange format. The Knowledge Engineering Review, 21(4), 293–316.Diaz-Agudo, B., & Gonzalez-Calero, P.A. (2007). Ontologies: A handbook of principles, concepts and applications in information systems, integrated series in information systems, chap. an ontological approach to develop knowledge intensive cbr systems (Vol. 14, pp. 173–214). Springer.Dung, P.M. (1995). On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming, and N -person games. Artificial Intelligence, 77, 321–357.Ferber, J., Gutknecht, O., Michel, F. (2004). From agents to organizations: An organizational view of multi-agent systems. In Agent-oriented software engineering VI, LNCS (Vol. 2935, pp. 214–230.) Springer-Verlag.Hadidi, N., Dimopolous, Y., Moraitis, P. (2010). Argumentative alternating offers. In 9th international conference on autonomous agents and multiagent systems, AAMAS-10 (pp. 441–448). IFAAMAS.Heras, S., Atkinson, K., Botti, V., Grasso, F., Julián, V., McBurney, P. (2010). How argumentation can enhance dialogues in social networks. In Proceedings of the 3rd international conference on computational models of argument, COMMA-10, frontiers in artificial intelligence and applications (Vol. 216, pp. 267–274). IOS Press.Heras, S., Botti, V., Julián, V. (2011). On a computational argumentation framework for agent societies. In Argumentation in multi-agent systems (pp. 123–140). Springer.Heras, S., Botti, V., Julián, V. (2012). Argument-based agreements in agent societies. Neurocomputing, 75(1), 156–162.Heras, S., Jordán, J., Botti, V., Julián, V. (2013). Argue to agree: A case-based argumentation approach. International Journal of Approximate Reasoning, 54(1), 82–108.Jordán, J., Heras, S., Julián, V. (2011). A customer support application using argumentation in multi-agent systems. In 14th international conference on information fusion (FUSION-11) (pp. 772– 778).Karunatillake, N.C. (2006). Argumentation-based negotiation in a social context. Ph.D. thesis, School of Electronics and Computer Science, University of Southampton, UK.Karunatillake, N.C., Jennings, N.R., Rahwan, I., McBurney, P. (2009). Dialogue games that agents play within a society. Artificial Intelligence, 173(9-10), 935–981.Kraus, S., Sycara, K., Evenchik, A. (1998). Reaching agreements through argumentation: a logical model and implementation. Artificial Intelligence, 104, 1–69.López de Mántaras, R., McSherry, D., Bridge, D., Leake, D., Smyth, B., Craw, S., Faltings, B., Maher, M.L., Cox, M., Forbus, K., Keane, M., Watson, I. (2006). Retrieval, reuse, revision, and retention in CBR. The Knowledge Engineering Review, 20(3), 215–240.Luck, M., & McBurney, P. (2008). Computing as interaction: Agent and agreement technologies. In IEEE international conference on distributed human-machine systems. IEEE Press.Oliva, E., McBurney, P., Omicini, A. (2008). Co-argumentation artifact for agent societies. In 5th international workshop on argumentation in multi-agent systems, Argmas-08 (pp. 31–46). Springer.Ontañón, S., & Plaza, E. (2007). Learning and joint deliberation through argumentation in multi-agent systems. In 7th international conference on agents and multi-agent systems, AAMAS-07. ACM Press.Ontañón, S., & Plaza, E. (2009). Argumentation-based information exchange in prediction markets. In Argumentation in multi-agent systems, LNAI (vol. 5384, pp. 181–196). Springer.Parsons, S., Sierra, C., Jennings, N.R. (1998). Agents that reason and negotiate by arguing. Journal of Logic and Computation, 8(3), 261–292.Prakken, H. (2010). An abstract framework for argumentation with structured arguments. Argument and Computation, 1, 93–124.Prakken, H., Reed, C., Walton, D. (2005). Dialogues about the burden of proof. In Proceedings of the 10th international conference on artificial intelligence and law, ICAIL-05 (pp. 115–124). ACM Press.Sierra, C., Botti, V., Ossowski, S. (2011). Agreement computing. KI - Künstliche Intelligenz 10.1007/s13218-010-0070-y .Soh, L.K., & Tsatsoulis, C. (2005). A real-time negotiation model and a multi-agent sensor network implementation. Autonomous Agents and Multi-Agent Systems, 11(3), 215–271.Walton, D., Reed, C., Macagno, F. (2008). Argumentation schemes. Cambridge University Press.Wardeh, M., Bench-Capon, T., Coenen, F.P. (2008). PISA - pooling information from several agents: Multiplayer argumentation from experience. In Proceedings of the 28th SGAI international conference on artificial intelligence, AI-2008 (pp. 133–146). Springer.Wardeh, M., Bench-Capon, T., Coenen, F.P. (2009). PADUA: A protocol for argumentation dialogue using association rules. AI and Law, 17(3), 183–215.Wardeh, M., Coenen, F., Bench-Capon, T. (2010). Arguing in groups. In 3rd international conference on computational models of argument, COMMA-10 (pp. 475–486). IOS Press.Willmott, S., Vreeswijk, G., Chesñevar, C., South, M., McGinnis, J., Modgil, S., Rahwan, I., Reed, C., Simari, G. (2006). Towards an argument interchange format for multi-agent systems. In 3rd international workshop on argumentation in multi-agent systems, ArgMAS-06 (pp. 17–34). Springer.Wyner, A., & Schneider, J. (2012). Arguing from a point of view. In Proceedings of the first international conference on agreement technologies

A dialogue game for agent resolving conflicts by verbal means

http://www.win.tue.nl/~evink/lcmas-2004-esslli.pdfInternational audienceWe present in this paper a formal framework for argumentation- based dialogues between agents. These latter manage the dialogues with the help of three components: an argumentative component to generate arguments, a social component to interprete arguments, and a conventional component to manage the sequence of coherent moves. We formalize the notion of dialogue-game to address the gap between individual moves and the extended sequence of coherent moves that arise between agents. The moves are not associated with an intention, however the dialogues have a goal