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-

An approach for Temporal Argumentation Using Labeled Defeasible Logic Programming (l-DeLP)

In the last decade, several argument-based formalisms have emerged, with application in many areas, such as legal reasoning, autonomous agents and multi-agent systems; many are based on Dung’s seminal work characterizing Abstract Argumentation Frameworks (AF). Recent research in the area has led to Temporal Argumentation Frameworks (TAF), that extend AF by considering the temporal availability of arguments. On the other hand, different more concrete argumentation systems exists, such as Defeasible Logic Programming (DeLP), specifying a knowledge representation language, and how arguments are built. In this work we combine time representation capabilities of TAF with the representation language and argument structure of DeLP, defining a rule-based argumentation framework that considers time at the object language level. In order to do this, we use an extension of DeLP, called Labeled DeLP (l-DeLP) to establish, for each program clause, the set of time intervals in which it is available, and to determine from this information the temporal availability of arguments. Acceptability semantics for TAF can then be applied to determine argument acceptability on timeFacultad de Informátic