Reasoning about constitutive norms in BDI agents

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Logic Journal of the IGPL following peer review. The definitive publisher-authenticated version: Criado Pacheco, N.; Argente Villaplana, E.; Noriega, P.; Botti Navarro, VJ. (2014). Reasoning about constitutive norms in BDI agents. Logic Journal of the IGPL. 22(1):66-93 is available online at: http://dx.doi.org/1093/jigpal/jzt035Software agents can be members of different institutions along their life; they might even belong to different institutions simultaneously. For these reasons, agents need capabilities that allow them to determine the repercussion that their actions would have within the different institutions. This association between the physical word, in which agents interactions and actions take place, and the institutional world is defined by means of constitutive norms. Currently, the problem of how agents reason about constitutive norms has been tackled from a theoretical perspective only. Thus, there is a lack of more practical proposals that allow the development of software agents capable of reasoning about constitutive norms. In this article we propose an information model, knowledge representation and an inference mechanism to enable Belief-Desire-Intention agents to reason about the consequences of their actions on the institutions and making decisions accordingly. Specifically, the information model, knowledge representation and inference mechanism proposed in this article allows agents to keep track of the institutional state given that they have a physical presence in some real-world environment. Agents have a limited and not fully believable knowledge of the physical world (i.e. they are placed in an uncertain environment). Therefore, our proposal also deals with the uncertainty of the environment.Criado Pacheco, N.; Argente Villaplana, E.; Noriega, P.; Botti Navarro, VJ. (2014). Reasoning about constitutive norms in BDI agents. Logic Journal of the IGPL. 22(1):66-93. doi:10.1093/jigpal/jzt035S6693221Baldi, P., Brunak, S., Chauvin, Y., Andersen, C. A. F., & Nielsen, H. (2000). Assessing the accuracy of prediction algorithms for classification: an overview. Bioinformatics, 16(5), 412-424. doi:10.1093/bioinformatics/16.5.412Bloch, I. (1996). Information combination operators for data fusion: a comparative review with classification. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 26(1), 52-67. doi:10.1109/3468.477860Casali, A., Godo, L., & Sierra, C. (2011). A graded BDI agent model to represent and reason about preferences. Artificial Intelligence, 175(7-8), 1468-1478. doi:10.1016/j.artint.2010.12.006Criado, N., Julián, V., Botti, V., & Argente, E. (2010). A Norm-Based Organization Management System. Lecture Notes in Computer Science, 19-35. doi:10.1007/978-3-642-14962-7_2Governatori, G., & Rotolo, A. (2008). BIO logical agents: Norms, beliefs, intentions in defeasible logic. Autonomous Agents and Multi-Agent Systems, 17(1), 36-69. doi:10.1007/s10458-008-9030-4Grossi, D., Aldewereld, H., Vázquez-Salceda, J., & Dignum, F. (2006). Ontological aspects of the implementation of norms in agent-based electronic institutions. Computational & Mathematical Organization Theory, 12(2-3), 251-275. doi:10.1007/s10588-006-9546-6Hübner, J. F., Boissier, O., Kitio, R., & Ricci, A. (2009). Instrumenting multi-agent organisations with organisational artifacts and agents. Autonomous Agents and Multi-Agent Systems, 20(3), 369-400. doi:10.1007/s10458-009-9084-yJONES, A. J. I., & SERGOT, M. (1996). A Formal Characterisation of Institutionalised Power. Logic Journal of IGPL, 4(3), 427-443. doi:10.1093/jigpal/4.3.427Rawls, J. (1955). Two Concepts of Rules. The Philosophical Review, 64(1), 3. doi:10.2307/2182230Da Silva, V. T. (2008). From the specification to the implementation of norms: an automatic approach to generate rules from norms to govern the behavior of agents. Autonomous Agents and Multi-Agent Systems, 17(1), 113-155. doi:10.1007/s10458-008-9039-

Reasoning about constitutive norms in BDI agents

Software agents can be members of different institutions along their life; they might even belong to different institutions simultaneously. For these reasons, agents need capabilities that allow them to determine the repercussion that their actions would have within the different institutions. This association between the physical word, in which agents' interactions and actions take place, and the institutional world is defined by means of constitutive norms. Currently, the problem of how agents reason about constitutive norms has been tackled from a theoretical perspective only. Thus, there is a lack of more practical proposals that allow the development of software agents capable of reasoning about constitutive norms. In this article we propose an information model, knowledge representation and an inference mechanism to enable Belief-Desire-Intention agents to reason about the consequences of their actions on the institutions and making decisions accordingly. Specifically, the information model, knowledge representation and inference mechanism proposed in this article allows agents to keep track of the institutional state given that they have a physical presence in some real-world environment. Agents have a limited and not fully believable knowledge of the physical world (i.e. they are placed in an uncertain environment). Therefore, our proposal also deals with the uncertainty of the environment. © The Author 2013. Published by Oxford University Press. All rights reserved

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Internet es, tal vez, el avance científico más relevante de nuestros días. Entre otras cosas, Internet ha permitido la evolución de los paradigmas de computación tradicionales hacia el paradigma de computaciónn distribuida, que se caracteriza por utilizar una red abierta de ordenadores. Los sistemas multiagente (SMA) son una tecnolog a adecuada para abordar los retos motivados por estos sistemas abiertos distribuidos. Los SMA son aplicaciones formadas por agentes heterog eneos y aut onomos que pueden haber sido dise~nados de forma independiente de acuerdo con objetivos y motivaciones diferentes. Por lo tanto, no es posible realizar ninguna hip otesis a priori sobre el comportamiento de los agentes. Por este motivo, los SMA necesitan de mecanismos de coordinaci on y cooperaci on, como las normas, para garantizar el orden social y evitar la aparici on de conictos. El t ermino norma cubre dos dimensiones diferentes: i) las normas como un instrumento que gu a a los ciudadanos a la hora de realizar acciones y actividades, por lo que las normas de nen los procedimientos y/o los protocolos que se deben seguir en una situaci on concreta, y ii) las normas como ordenes o prohibiciones respaldadas por un sistema de sanciones, por lo que las normas son medios para prevenir o castigar ciertas acciones. En el area de los SMA, las normas se vienen utilizando como una especi caci on formal de lo que est a permitido, obligado y prohibido dentro de una sociedad. De este modo, las normas permiten regular la vida de los agentes software y las interacciones entre ellos. La motivaci on principal de esta tesis es permitir a los dise~nadores de los SMA utilizar normas como un mecanismo para controlar y coordinar SMA abiertos. Nuestro objetivo es elaborar mecanismos normativos a dos niveles: a nivel de agente y a nivel de infraestructura. Por lo tanto, en esta tesis se aborda primero el problema de la de nici on de agentes normativos aut onomos que sean capaces de deliberar acercaCriado Pacheco, N. (2012). Using Norms To Control Open Multi-Agent Systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/17800Palanci

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