Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-28T14:04:25.589Z Has data issue: false hasContentIssue false

Answer set programming and agents

Published online by Cambridge University Press:  05 November 2018

Abeer Dyoub
Affiliation:
Dipartimento di Ingegneria e Scienze dell’Informazione e Matematica, Universit’a degli Studi dell’Aquila, Via Vetoio 1, Loc. Coppito, I-67100 L’Aquila, Italy e-mail: [email protected], stefania.costantini, [email protected]
Stefania Costantini
Affiliation:
Dipartimento di Ingegneria e Scienze dell’Informazione e Matematica, Universit’a degli Studi dell’Aquila, Via Vetoio 1, Loc. Coppito, I-67100 L’Aquila, Italy e-mail: [email protected], stefania.costantini, [email protected]
Giovanni De Gasperis
Affiliation:
Dipartimento di Ingegneria e Scienze dell’Informazione e Matematica, Universit’a degli Studi dell’Aquila, Via Vetoio 1, Loc. Coppito, I-67100 L’Aquila, Italy e-mail: [email protected], stefania.costantini, [email protected]

Abstract

In this paper, we discuss the potential role of answer set programming (ASP) in the context of approaches to the development of agents and multi-agent systems especially in the realm of Computational Logic. After shortly recalling the main (computational-logic-based) agent-oriented frameworks, we introduce ASP; then, we discuss the usefulness of a potential integration of the two paradigms in a modular heterogeneous framework, and the feasibility of such integration. This also in the more general view of improving and empowering flexibility of agent-oriented frameworks. Relevant literature will be mentioned and discussed. Possible future directions and potential developments will be outlined.

Type
Principles and Practice of Multi-Agent Systems
Copyright
© Cambridge University Press, 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aielli, F., Ancona, D., Caianiello, P., Costantini, S., De Gasperis, G., Marco, A. D., Ferrando, A. & Mascardi, V. 2016. FRIENDLY & KIND with your health: human-friendly knowledge-intensive dynamic systems for the e-health domain. In ‘PAAMS (Workshops)’, Communications in Computer and Information Science, 616, 15–26. Springer.Google Scholar
Akbari, O. Z. 2010. A survey of agent-oriented software engineering paradigm: towards its industrial acceptance. Journal of Computer Engineering Research 1(2), 1428.Google Scholar
Alviano, M., Faber, W., Greco, G. & Leone, N. 2012. Magic sets for disjunctive datalog programs. Artificial Intelligence 187, 156192.Google Scholar
Ambros-Ingerson, J. A. & Steel, S. 1988. Integrating planning, execution and monitoring. In Proceedings of the 7th National Conference on Artificial Intelligence, 83–88, August 21–26.Google Scholar
Amendola, G., Greco, G., Leone, N. & Veltri, P. 2016. Modeling and reasoning about NTU games via answer set programming. In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI 2016, 38–45. IJCAI/AAAI Press, July 9–15.Google Scholar
Anderson, J. R. & Lebiere, C. 1998. The Atomic Components of Thought. Lawrence Erlbaum Associates.Google Scholar
Apt, K. R. & Bol, R. N. 1994. Logic programming and negation: a survey. Journal of Logic Programming 19/20, 972.Google Scholar
Aschinger, M., Drescher, C., Friedrich, G., Gottlob, G., Jeavons, P., Ryabokon, A. & Thorstensen, E. 2011. Optimization methods for the partner units problem. In Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems - 8th International Conference, CPAIOR 2011. Proceedings, T. Achterberg and J. C. Beck (eds), ‘Lecture Notes in Computer Science 6697, 4–19. Springer.Google Scholar
Baldoni, M., Baroglio, C., Mascardi, V., Omicini, A. & Torroni, P. 2010. Agents, multi-agent systems and declarative programming: what, when, where, why, who, how? In A 25-Year Perspective on Logic Programming, Dovier, A. & Pontelli, E. (eds). Springer-Verlag, 204–230.Google Scholar
Balduccini, M. 2007 a. Learning action descriptions with a-prolog: action language c. In AAAI Spring Symposium: Logical Formalizations of Commonsense Reasoning, AAAI, Technical Report SS-07-05, 13–18.Google Scholar
Balduccini, M. 2007 b. Modules and signature declarations for a-prolog: progress report. In Workshop on Software Engineering for Answer Set Programming (SEA’07), 41–55.Google Scholar
Balduccini, M. & Gelfond, M. 2003. Diagnostic reasoning with a-prolog. Theory and Practice of Logic Programming 3(4), 425461.Google Scholar
Balduccini, M. & Gelfond, M. 2008. The AAA architecture: an overview. In Architectures for Intelligent Theory-Based Agents, Papers from the 2008 AAAI Spring Symposium, Technical Report SS-08-02, 1–6. AAAI, March 26–28.Google Scholar
Balduccini, M., Gelfond, M. & Nogueira, M. 2006. Answer set based design of knowledge systems. Annals of Mathematics and Artificial Intelligence 47(1–2), 183219.Google Scholar
Balduccini, M., Regli, W. C. & Nguyen, D. N. 2014. An ASP-based architecture for autonomous UAVs in dynamic environments: Progress report, CoRR abs/1405.1124.Google Scholar
Baral, C. 2003. Knowledge Representation, Reasoning and Declarative Problem Solving. Cambridge University Press.Google Scholar
Baral, C., Dzifcak, J. & Takahashi, H. 2006. Macros, macro calls and use of ensembles in modular answer set programming. In Logic Programming, 376–390. Springer.Google Scholar
Baral, C., Gelfond, G., Son, T. C. & Pontelli, E. 2010. Using answer set programming to model multi-agent scenarios involving agents’ knowledge about other’s knowledge. In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: Volume 1, 259–266. International Foundation for Autonomous Agents and Multiagent Systems.Google Scholar
Baral, C. & Gelfond, M. 2000. Reasoning agents in dynamic domains. In Logic-Based Artificial Intelligence, van der Hoek, W., Kaminka, G. A., Lespérance, Y., Luck, M. & Sen, S. (eds). Springer, 257–279.Google Scholar
Bauer, B., Müller, J. P. & Odell, J. 2001. Agent UML: a formalism for specifying multiagent software systems. International Journal of Software Engineering and Knowledge Engineering 11(3), 207230.Google Scholar
Bauters, K. 2011 a. Modeling coalition formation using multi-focused answer sets. In Proceedings of ESSLLI, 11, 25–33.Google Scholar
Bauters, K. 2011 b. Modeling negotiation using multi-focused answer sets. In 2011 European Summer School in Logic, Language and Information (ESSLLI 2011): Student session, 25–33.Google Scholar
Bauters, K., Janssen, J., Schockaert, S., De Cock, M. & Vermeir, D. 2010. Communicating answer set programs. In 26th International Conference of Logic Programming (ICLP 2010), 7, 34–43. Schloss Dagstuhl–Leibniz-Zentrum für Informatik.Google Scholar
Bauters, K., Schockaert, S., Janssen, J., Vermeir, D. & De Cock, M. 2013. Expressiveness of communication in answer set programming. Theory and Practice of Logic Programming 13(3), 361394.Google Scholar
Belardinelli, F., Lomuscio, A. & Patrizi, F. 2014. Verification of agent-based artifact systems. Journal of Artificial Intelligence Research 51, 333376.Google Scholar
Blount, J., Gelfond, M. & Balduccini, M. 2015. A theory of intentions for intelligent agents - (extended abstract). In Proceedings of the 13th International Conference on Logic Programming and Nonmonotonic Reasoning LPNMR 2015, Lecture Notes in Computer Science 9345, 134–142. Springer.Google Scholar
Borchert, P., Anger, C., Schaub, T. & Truszczynski, M. 2004. Towards systematic benchmarking in answer set programming: the dagstuhl initiative. In Proceedings of the International Conference on Logic Programming and Nonmonotonic Reasoning LPNMR 2004, Lecture Notes in Computer Science 2923, 3–7. Springer.Google Scholar
Bordini, R. H., Braubach, L., Dastani, M., Fallah-Seghrouchni, A. E., Gómez-Sanz, J. J., Leite, J., O’Hare, G. M. P., Pokahr, A. & Ricci, A. 2006. A survey of programming languages and platforms for multi-agent systems. Informatica (Slovenia) 30(1), 3344.Google Scholar
Bordini, R. H. & Hübner, J. F. 2006. BDI agent programming in AgentSpeak using Jason (tutorial paper). In Computational Logic in Multi-Agent Systems, 6th International Workshop, CLIMA VI, Revised Selected and Invited Papers, F. Toni and P. Torroni (eds), LNCS 3900. Springer, 143–164.Google Scholar
Bordini, R. H., Hübner, J. F. & Wooldridge, M. 2007. Programming Multi-Agent Systems in AgentSpeak Using Jason. John Wiley & Sons. Wiley Series in Agent Technology.Google Scholar
Börger, E. & Stärk, R. F. 2003. Abstract State Machines. A Method for High-Level System Design and Analysis. Springer.Google Scholar
Bracciali, A., Demetriou, N., Endriss, U., Kakas, A., Lu, W., Mancarella, P., Sadri, F., Stathis, K., Terreni, G. & Toni, F. 2005. The KGP model of agency: computational model and prototype implementation. In Global Computing: IST/FET Intl. Workshop, Revised Selected Papers, LNAI 3267, Springer-Verlag, 340–367.Google Scholar
Bratman, M. E. 1999. Intention, Plans, and Practical Reason. Cambridge University Press.Google Scholar
Bratman, M. E., Israel, D. J. & Pollack, M. E. 1988. Plans and resource-bounded practical reasoning. Computational Intelligence 4(3), 349355.Google Scholar
Brewka, G., Eiter, T. & Fink, M. 2011a. Nonmonotonic multi-context systems: a flexible approach for integrating heterogeneous knowledge sources. In Logic Programming, Knowledge Representation, and Nonmonotonic Reasoning - Essays Dedicated to Michael Gelfond on the Occasion of His 65th Birthday, M. Balduccini and T. C. Son (eds), Lecture Notes in Computer Science 6565. Springer, 233–258.Google Scholar
Brewka, G., Eiter, T., Fink, M. & Weinzierl, A. 2011b. Managed multi-context systems. In IJCAI 2011, Proceedings of the 22nd International Joint Conference on Artificial Intelligence, T. Walsh (ed.), 786–791. IJCAI/AAAI.Google Scholar
Brewka, G., Ellmauthaler, S. & Pührer, J. 2014. Multi-context systems for reactive reasoning in dynamic environments. In ECAI 2014, Proceedings of the 21st European Conference on Artificial Intelligence, T. Schaub (ed.), 159–164. IJCAI/AAAI.Google Scholar
Brogi, A., Mancarella, P., Pedreschi, D. & Turini, F. 1994. Modular logic programming. ACM Transactions on Programming Languages and Systems (TOPLAS) 16(4), 13611398.Google Scholar
Brooks, D. R., Erdem, E., Erdogan, S. T., Minett, J. W. & Ringe, D. 2007. Inferring phylogenetic trees using answer set programming. Journal of Automated Reasoning 39(4), 471511.Google Scholar
Brooks, R. A. 1986. A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation 2(1), 1423.Google Scholar
Brustoloni, J. C. 1991. Autonomous Agents: Characterization and Requirements, Technical report, Carnegie Mellon University.Google Scholar
Buccafurri, F. & Caminiti, G. 2005. A social semantics for multi-agent systems. In Logic Programming and Nonmonotonic Reasoning, 317–329. Springer.Google Scholar
Buccafurri, F. & Gottlob, G. 2002. Multiagent compromises, joint fixpoints, and stable models. In Computational Logic: Logic Programming and Beyond, Essays in Honour of Robert A. Kowalski, Part I, A. C. Kakas and F. Sadri (eds), Lecture Notes in Computer Science 2407, 561–585. Springer.Google Scholar
Bugliesi, M., Lamma, E. & Mello, P. 1994. Modularity in logic programming. The Journal of Logic Programming, Elsevier 19, 443502.Google Scholar
Castellucci, A., Ianni, G., Vasile, D. & Costa, S. 2001. Searching and surfing the web using a semi-adaptive meta-engine. In 2001 International Symposium on Information Technology (ITCC 2001), 416–420. IEEE Computer Society, April 2–4.Google Scholar
Cliffe, O., De Vos, M. & Padget, J. 2006. Answer set programming for representing and reasoning about virtual institutions. In Computational Logic in Multi-Agent Systems, 60–79. Springer.Google Scholar
Coen, M. H. 1994. Sodabot: a software agent environment and construction system. In Proceedings of the 12th National Conference on Artificial Intelligence, Volume 2, 1433. AAAI Press/MIT Press.Google Scholar
Cohen, P. R., Greenberg, M. L., Hart, D. M. & Howe, A. E. 1989. Trial by fire: understanding the design requirements for agents in complex environments. AI Magazine 10(3), 3248.Google Scholar
Cortés, U., Tolchinsky, P., Nieves, J., López-Navidad, A. & Caballero, F. 2005. Arguing the discard of organs for tranplantation in CARREL In CATAI 2005, 93–105.Google Scholar
Costantini, S. 1995. Contributions to the stable model semantics of logic programs with negation. Theoretical Computer Science 149(2), 231255.Google Scholar
Costantini, S. 2006. On the existence of stable models of non-stratified logic programs. Theory and Practice of Logic Programming 6(1–2), 169212.Google Scholar
Costantini, S. 2011. Answer set modules for logical agents. In Datalog Reloaded - First International Workshop, Datalog 2010. Revised Selected Papers, O. de Moor, G. Gottlob, T. Furche and A. J. Sellers (eds), Lecture Notes in Computer Science 6702, 37–58. Springer.Google Scholar
Costantini, S. 2015 a. ACE: a flexible environment for complex event processing in logical agents. In Engineering Multi-Agent Systems, Third International Workshop, EMAS 2015, Revised Selected Papers, M. Baldoni, L. Baresi and M. Dastani (eds), Lecture Notes in Computer Science 9318, 70–91. Springer.Google Scholar
Costantini, S. 2015 b. Knowledge acquisition via non-monotonic reasoning in distributed heterogeneous environments. In Proceedings of the 13th International Conference on Logic Programming and Nonmonotonic Reasoning LPNMR 2015, M. Truszczyński, G. Ianni and F. Calimeri, (eds), Lecture Notes in Computer Science 9345, 228–241. Springer.Google Scholar
Costantini, S., D’Antona, O. M. & Provetti, A. 2002. On the equivalence and range of applicability of graph-based representations of logic programs. Information Processing Letters 84(5), 241249.Google Scholar
Costantini, S., De Gasperis, G. & Nazzicone, G. 2017. DALI for cognitive robotics: principles and prototype implementation. In Practical Aspects of Declarative Languages - 19th International Symposium, Proceedings, Y. Lierler and W. Taha (eds), Lecture Notes in Computer Science 10137, 152–162. Springer.Google Scholar
Costantini, S. & De Gasperis, G. 2015. Exchanging data and ontological definitions in multi-agent-contexts systems. In Challenge+DC@RuleML, CEUR Workshop Proceedings 1417. CEUR-WS.org.Google Scholar
Costantini, S., De Gasperis, G. & Nazzicone, G. 2015. Exploration of unknown territory via DALI agents and ASP modules. In Distributed Computing and Artificial Intelligence, 12th International Conference, DCAI 2015, S. Omatu, Q. M. Malluhi, S. Rodríguez-González, G. Bocewicz, E. Bucciarelli, G. Giulioni and F. Iqba (eds), Advances in Intelligent Systems and Computing 373, 285–292. Springer.Google Scholar
Costantini, S., De Gasperis, G., Pitoni, V. & Salutari, A. 2017. DALI: a multi agent system framework for the web, cognitive robotic and complex event processing. In Proceedings of the 32nd Italian Conference on Computational Logic, CEUR Workshop Proceedings 1949, 286–300. CEUR-WS.org. http://ceur-ws.org/Vol-1949/CILCpaper05.pdf Google Scholar
Costantini, S. & Formisano, A. 2010. Answer set programming with resources. Journal of Logic and Computation 20(2), 533571.Google Scholar
Costantini, S. & Formisano, A. 2011. Weight constraints with preferences in ASP. In Proceedings of the 11th International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR 2011), Lecture Notes in Computer Science 6645. Springer.Google Scholar
Costantini, S. & Formisano, A. 2013. ‘RASP and ASP as a fragment of linear logic’. Journal of Applied Non-Classical Logics 23(1–2), 4974.Google Scholar
Costantini, S. & Formisano, A. 2016. Augmenting agent computational environments with quantitative reasoning modules and customizable bridge rules. In Autonomous Agents and Multiagent Systems - AAMAS 2016 Workshops, - Visionary Papers, Revised Selected Papers, Lecture Notes in Computer Science 10003, 104–121.Google Scholar
Costantini, S., Formisano, A. & Petturiti, D. 2010. Extending and implementing RASP. Fundamenta Informaticae. 105(1–2), 133.Google Scholar
Costantini, S. & Tocchio, A. 2002. A logic programming language for multi-agent systems. In Logics in Artificial Intelligence, Proceedings of the 8th European Conference, JELIA 2002, LNAI 2424, 1–13. Springer-Verlag.Google Scholar
Costantini, S. & Tocchio, A. 2004. The DALI logic programming agent-oriented language. In Logics in Artificial Intelligence, Proceedings of the 9th European Conference, Jelia 2004, LNAI 3229, 685–688. Springer-Verlag.Google Scholar
Costantini, S. & Tocchio, A. 2005. Learning by knowledge exchange in logical agents. In WOA 2005: Dagli Oggetti agli Agenti. 6th AI*IA/TABOO Joint Workshop “From Objects to Agents”: Simulation and Formal Analysis of Complex Systems, F. D. Paoli, E. Merelli and A. Omicini (eds). Pitagora Editrice Bologna, 1–8.Google Scholar
Costantini, S. & Tocchio, A. 2008. DALI: an architecture for intelligent logical agents. In AAAI Spring Symposium: Emotion, Personality, and Social Behavior, 13–18. AAAI.Google Scholar
Dantsin, E., Eiter, T., Gottlob, G. & Voronkov, A. 2001. Complexity and expressive power of logic programming. ACM Computing Surveys 33(3), 374425.Google Scholar
Dao-Tran, M., Eiter, T., Fink, M. & Krennwallner, T. 2009. Modular nonmonotonic logic programming revisited. In Logic Programming, 145–159. Springer.Google Scholar
Dastani, M. 2008. 2APL: a practical agent programming language, Autonomous Agents and Multi-Agent Systems 16(3), 214–248.Google Scholar
Dastani, M. 2015. Programming multi-agent systems. Knowledge Engineering Review 30(4), 394418.Google Scholar
Dastani, M., van Birna Riemsdijk, M. & Meyer, J.-J. C. 2005. Programming multi-agent systems in 3APL. In Multi-Agent Programming, 39–67. Springer.Google Scholar
Dastani, M., Van Riemsdijk, M. B., Hulstijn, J., Dignum, F. & Meyer, J.-J. C. 2004. Enacting and deacting roles in agent programming. In Agent-oriented software engineering V, 189–204. Springer.Google Scholar
De Gasperis, G., Costantini, S. & Nazzicone, G. 2014. Dali multi agent systems framework, doi 10.5281/zenodo.11042, DALI GitHub Software Repository. DALI. http://github.com/AAAI-DISIM-UnivAQ/DALI Google Scholar
De Vos, M., Cliffe, O., Watson, R., Crick, T., Padget, J. A., Needham, J. & Brain, M. 2005. T-laima: answer set programming for modelling agents with trust. In EUMAS, Koninklijke Vlaamse Academie van Belie voor Wetenschappen en Kunsten, 126–136.Google Scholar
De Vos, M. & Vermeir, D. 2004. Extending answer sets for logic programming agents. Annals of Mathematics and Artificial Intelligence, Springer 42(1–3), 103139.Google Scholar
d’Inverno, M., Hindriks, K. & Luck, M. 2000. A formal architecture for the 3APL agent programming language. In ZB 2000: Formal Specification and Development in Z and B, First International Conference of B and Z Users, York, UK, August 29 - September 2, 2000, Proceedings, 168–187. Springer.Google Scholar
d’Inverno, M. & Luck, M. 1998. Engineering agentspeak (l): a formal computational model. Journal of Logic and Computation 8(3), 233260.Google Scholar
Dix, J., Eiter, T., Kraus, S., Ozcan, F. & Subrahmanian, V. S. 2000. Heterogeneous agent systems. The MIT Press.Google Scholar
Duch, W., Oentaryo, R. J. & Pasquier, M. 2008. Cognitive architectures: Where do we go from here? In AGI Conference, 171, 122–136. IOS Press.Google Scholar
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(2), 321358.Google Scholar
Eiter, T., Gottlob, G. & Veith, H. 1997. Modular logic programming and generalized quantifiers. In Logic Programming and Nonmonotonic Reasoning, 289–308. Springer.Google Scholar
Erdem, E., Aker, E. & Patoglu, V. 2012. Answer set programming for collaborative housekeeping robotics: representation, reasoning, and execution. Intelligent Service Robotics 5(4), 275291.Google Scholar
Erdem, E., Erdem, Y., Erdogan, H. & Öztok, U. 2011. Finding answers and generating explanations for complex biomedical queries. In Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2011, W. Burgard and D. Roth, (eds). AAAI Press, August 7–11.Google Scholar
Erdem, E., Gelfond, M. & Leone, N. 2016. Applications of answer set programming. AI Magazine 37(3), 5368.Google Scholar
Erdem, E. & Öztok, U. 2015. Generating explanations for biomedical queries. Theory and Practice of Logic Programming 15(1), 3578.Google Scholar
Erdem, E., Patoglu, V. & Saribatur, Z. G. 2015. Integrating hybrid diagnostic reasoning in plan execution monitoring for cognitive factories with multiple robots. In IEEE International Conference on Robotics and Automation, ICRA 2015, 2007–2013. IEEE, May 26–30.Google Scholar
Erdem, E., Patoglu, V., Saribatur, Z. G., Schüller, P. & Uras, T. 2013. ‘Finding optimal plans for multiple teams of robots through a mediator: a logic-based approach’. Theory and Practice of Logic Programming 13(4–5), 831846.Google Scholar
Etzioni, O., Lesh, N. & Segal, R. 1994. Building Softbots for Unix (Preliminary Report). Technical report. AAAI Press.Google Scholar
Faber, W., Greco, G. & Leone, N. 2007. Magic sets and their application to data integration. Journal of Computer and System Sciences 73(4), 584609.Google Scholar
Faber, W. & Woltran, S. 2009. Manifold answer-set programs for meta-reasoning. In Logic Programming and Nonmonotonic Reasoning, 115–128. Springer.Google Scholar
Febbraro, O., Leone, N., Grasso, G. & Ricca, F. 2012. JASP: a framework for integrating answer set programming with java. In Principles of Knowledge Representation and Reasoning: Proceedings of the Thirteenth International Conference, KR 2012. AAAI Press, June 10–14.Google Scholar
Febbraro, O., Reale, K. & Ricca, F. 2011. ASPIDE: integrated development environment for answer set programming. In Logic Programming and Nonmonotonic Reasoning, 317–330. Springer.Google Scholar
Ferguson, I. A. 1992. Touring machines: autonomous agents with attitudes. IEEE Computer 25(5), 5155.Google Scholar
Fikes, R. E. & Nilsson, N. J. 1971. STRIPS: a new approach to the application of theorem proving to problem solving. Artificial intelligence 2(3–4), 189208.Google Scholar
Fisher, M. 1994. A survey of concurrent METATEM the language and its applications. In Temporal Logic 480–505. Springer.Google Scholar
Fisher, M. 1998. Representing abstract agent architectures. In Intelligent Agents V: Agents Theories, Architectures, and Languages, 227–241. Springer.Google Scholar
Fisher, M., Bordini, R. H., Hirsch, B. & Torroni, P. 2007. Computational logics and agents: a road map of current technologies and future trends. Computational Intelligence Journal 23(1), 6191.Google Scholar
Formisano, A. & Petturiti, D. 2010. RASP and P-RASP: an implementation. http://www.dmi.unipg.it/formis/raspberry/ Google Scholar
Franklin, S. & Graesser, A. C. 1996. Is it an agent, or just a program?: A taxonomy for autonomous agents. In Intelligent Agents III, Agent Theories, Architectures, and Languages, ECAI ’96 Workshop (ATAL), Budapest, Hungary, August 12-13, 1996, Proceedings, 21–35. Springer.Google Scholar
Friedrich, G., Fugini, M., Mussi, E., Pernici, B. & Tagni, G. 2010. Exception handling for repair in service-based processes. IEEE Transactions on Software Engineering 36(2), 198215.Google Scholar
Friedrich, G., Ryabokon, A., Falkner, A. A., Haselböck, A., Schenner, G. & Schreiner, H. 2011. (Re)configuration based on model generation. In Proceedings Second Workshop on Logics for Component Configuration, LoCoCo 2011, C. Drescher, I. Lynce and R. Treinen (eds), EPTCS 65, 26–35, September 12.Google Scholar
Gaifman, H. & Shapiro, E. 1989. Fully abstract compositional semantics for logic programs. In Proceedings of the 16th ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, 134–142. ACM.Google Scholar
Gallucci, L. & Ricca, F. 2007. Visual querying and application programming interface for an ASP-based ontology language. Proceedings of SEA 7, 5670.Google Scholar
Gebser, M., Schaub, T., Thiele, S. & Veber, P. 2011. Detecting inconsistencies in large biological networks with answer set programming. Theory and Practice of Logic Programming 11(2–3), 323360.Google Scholar
Gelfond, M. 2004. Answer set programming and the design of deliberative agents. In Logic Programming, Proceedings of the 20th International Conference, ICLP 2004, B. Demoen and V. Lifschitz (eds), Lecture Notes in Computer Science 3132, 19–26. Springer.Google Scholar
Gelfond, M. 2008. Answer sets. In Handbook of Knowledge Representation. Chapter 7, van Harmelen F., Lifschitz V. & Porter B. W. (eds). Foundations of Artificial Intelligence 3, 285–316. Elsevier.Google Scholar
Gelfond, M. & Kahl, Y. 2014. Knowledge Representation, Reasoning, and the Design of Intelligent Agents: The Answer-Set Programming Approach. Cambridge University Press.Google Scholar
Gelfond, M. & Lifschitz, V. 1988. The stable model semantics for logic programming. In Proceedings of the 5th International Conference and Symposium on Logic Programming, R. Kowalski and K. Bowen (eds), 1070–1080. MIT Press.Google Scholar
Gelfond, M. & Lifschitz, V. 1991. Classical negation in logic programs and disjunctive databases. New Generation Computing 9, 365385.Google Scholar
Gelfond, M. & Lifschitz, V. 1998. Action languages. Electronic Transactions on Artificial Intelligence 2, 193210.Google Scholar
Georgeff, M., Pell, B., Pollack, M., Tambe, M. & Wooldridge, M. 1998. The belief-desire-intention model of agency. In Intelligent Agents V: Agents Theories, Architectures, and Languages, 5th International Workshop, ATAL ’98, Paris, France, July 4-7, 1998, Proceedings, 1–10. Springer.Google Scholar
Gero, J. S. & Peng, W. 2009. Understanding behaviors of a constructive memory agent: a Markov chain analysis. Knowledge-Based Systems 22(8), 610621.Google Scholar
Giordano, L. & Martelli, A. 1994. Structuring logic programs: a modal approach. The Journal of Logic Programming 21(2), 5994.Google Scholar
Giunchiglia, E., Lee, J., Lifschitz, V., McCain, N. & Turner, H. 2004. Nonmonotonic causal theories. Artificial Intelligence 153(1), 49104.Google Scholar
Gonçalves, R., Knorr, M. & Leite, J. 2014. Evolving bridge rules in evolving multi-context systems. In Computational Logic in Multi-Agent Systems - 15th International Workshop, CLIMA XV. Proceedings, N. Bulling, L. W. N. van der Torre, S. Villata, W. Jamroga and W. W. Vasconcelos (eds), 52–69.Google Scholar
Grasso, G., Leone, N. & Ricca, F. 2013. Answer set programming: language, applications and development tools. In Web Reasoning and Rule Systems - 7th International Conference, RR 2013, Proceedings, W. Faber and D. Lembo (eds), Lecture Notes in Computer Science 7994. Springer.Google Scholar
Greco, G. & Terracina, G. 2013. Frequency-based similarity for parameterized sequences: formal framework, algorithms, and applications. Information Science 237, 176195.Google Scholar
Havur, G., Ozbilgin, G., Erdem, E. & Patoglu, V. 2014. Geometric rearrangement of multiple movable objects on cluttered surfaces: a hybrid reasoning approach. In 2014 IEEE International Conference on Robotics and Automation, ICRA 2014, 445–452. IEEE, May 31 to June 7.Google Scholar
Hindriks, K. 2008. Modules as policy-based intentions: modular agent programming in GOAL. In Proceedings of the 5th International Conference on Programming Multi-agent Systems ProMAS07, 156–171. Springer.http://dl.acm.org/citation.cfm?id=1793534.1793546 Google Scholar
Hindriks, K. V., De Boer, F. S., Van der Hoek, W. & Meyer, J.-J. C. 1999. Agent programming in 3APL, Autonomous Agents and Multi-Agent Systems 2(4): 357–401.Google Scholar
Hindriks, K. V., De Boer, F. S., Van Der Hoek, W. & Meyer, J.-J. C. 2000. Agent programming with declarative goals. In Intelligent Agents VII, Agent Theories Architectures and Languages, 228–243. Springer.Google Scholar
Hübner, J. F., Sichman, J. S. & Boissier, O. 2007. Developing organised multiagent systems using the MOISE. IJAOSE 1(3/4), 370395.Google Scholar
Ianni, G. 2001. Intelligent anticipated exploration of web sites. AI Communications 14(4), 197214.Google Scholar
Ianni, G., Calimeri, F., Lio, V. & Galizia, S. 2003. Reasoning about the semantic web using answer set programming. In Proceedings of the 2003 Joint Conference on Declarative Programming, AGP-2003, F. Buccafurri (ed.), 324–336.Google Scholar
Ianni, G., Ielpa, G., Pietramala, A., Santoro, M. C. & Calimeri, F. 2004. Enhancing answer set programming with templates. In 10th International Workshop on Non-Monotonic Reasoning (NMR 2004), Proceedings, 233–239.Google Scholar
JADE website 2016. Available at http://jade.tilab.com/ Google Scholar
Janhunen, T., Oikarinen, E., Tompits, H. & Woltran, S. 2009. Modularity aspects of disjunctive stable models. Journal of Artificial Intelligence Research 35, 813857.Google Scholar
Jennings, N. R. 1993. Specification and implementation of a belief-desire-joint-intention architecture for collaborative problem solving. International Journal of Intelligent and Cooperative Information Systems, World Scientific 2(3), 289318.Google Scholar
Jennings, N. R., Sycara, K. & Wooldridge, M. 1998. A roadmap of agent research and development. Autonomous Agents and Multi-Agent Systems 1(1), 738.Google Scholar
Juneidi, S. J. & Vouros, G. A. 2004. Survey and evaluation of agent oriented software engineering. In IASTED International Conference on Software Engineering, part of the 22nd Multi-Conference on Applied Informatics, 2004, M. H. Hamza (ed.), 433–440. IASTED/ACTA Press.Google Scholar
Kaelbling, L. P. 1991. A situated-automata approach to the design of embedded agents. SIGART Bulletin 2(4), 8588.Google Scholar
Kakas, A. C., Mancarella, P., Sadri, F., Stathis, K. & Toni, F. 2004. The KGP model of agency. In Proceedings of the 16th Eureopean Conference on Artificial Intelligence, ECAI 2004, R. L. de Mántaras and L. Saitta (eds), 33–37. IOS Press.Google Scholar
Kautz, H. A. & Selman, B. 1992. Planning as satisfiability. In ECAI, 359–363.Google Scholar
Keil, F. 1989. Concepts, Kinds, and Cognitive Development. The MIT Press.Google Scholar
Khaitan, S. K. & McCalley, J. D. 2015. Design techniques and applications of cyberphysical systems: a survey. IEEE Systems Journal 9(2), 350365.Google Scholar
Kinny, D., Georgeff, M. P. & Rao, A. S. 1996. A methodology and modelling technique for systems of BDI agents. In Agents Breaking Away, 7th European Workshop on Modelling Autonomous Agents in a Multi-Agent World, Proceedings, W. V. de Velde and J. W. Perram (eds), Lecture Notes in Computer Science 1038, 56–71. Springer.Google Scholar
Kouvaros, P. & Lomuscio, A. 2016. Parameterised verification for multi-agent systems. Artificial Intelligence. 234, 152189.Google Scholar
Kowalski, R. & Sadri, F. 1996. Towards a unified agent architecture that combines rationality with reactivity. In Logic in Databases, Lecture Notes in Computer Science 1154, 135–149. Springer.Google Scholar
Laird, J. 2012. The SOAR Cognitive Architecture. MIT Press.Google Scholar
Laird, J. E. 2008. Extending the SOAR cognitive architecture. In Proceedings of the First Artificial General Intelligence Conference, 224–235.Google Scholar
Laird, J. E., Newell, A. & Rosenbloom, P. S. 1987. Soar: an architecture for general intelligence. Artificial Intelligence 33(1), 164.Google Scholar
Langley, P. 2005. An adaptive architecture for physical agents. In The 2005 IEEE/WIC/ACM International Conference on Web Intelligence, 2005. Proceedings, 18–25. IEEE.Google Scholar
Langley, P., Laird, J. E. & Rogers, S. 2009. Cognitive architectures: research issues and challenges. Cognitive Systems Research 10(2), 141160.Google Scholar
Leite, J.-A. 2003. Evolving knowledge bases: specification and semantics, Frontiers in Artificial Intelligence and Applications, 81. IOS Press.Google Scholar
Leite, J., Alferes, J. J. & Mito, B. 2009. Resource allocation with answer-set programming. In 8th International Joint Conference on Autonomous Agents and Multiagent Systems AAMAS 2009, Proceedings, C. Sierra and C. Castelfranchi and K. S. Decker and J. Simão Sichman (eds), 649–656. IFAAMAS.Google Scholar
Leite, J. A., Alferes, J. J. & Pereira, L. M. 2001. MINERVA - a dynamic logic programming agent architecture. In Intelligent Agents VIII, 8th International Workshop, ATAL 2001, Revised Papers, J. C. Meyer and M. Tambe, (eds), Lecture Notes in Computer Science 2333, 141–157. Springer.Google Scholar
Leone, N. 2007. Logic programming and nonmonotonic reasoning: from theory to systems and applications. In Proceedings of the 11th International Conference on Logic Programming and Nonmonotonic Reasoning LPNMR 2007, Lecture Notes in Computer Science 4483, 1. Springer.Google Scholar
Leone, N. & Ricca, F. 2015. Answer set programming: a tour from the basics to advanced development tools and industrial applications. In Reasoning Web. Web Logic Rules - 11th International Summer School 2015, Tutorial Lectures, W. Faber and A. Paschke, (eds), Lecture Notes in Computer Science 9203, 308–326. Springer.Google Scholar
Lierler, Y. & Truszczyński, M. 2013. Modular answer set solving, Late-Breaking Developments in the Field of Artificial Intelligence, WS-13-17. AAAI Press.Google Scholar
Lifschitz, V. 1999. Action languages, answer sets, and planning. In The Logic Programming Paradigm, 357–373. Springer.Google Scholar
Lifschitz, V. & Ren, W. 2006. A modular action description language. In Proceedings, The Twenty-First National Conference on Artificial Intelligence and the Eighteenth Innovative Applications of Artificial Intelligence Conference, 6, 853–859. AAAI Press.Google Scholar
Lifschitz, V. & Turner, H. 1994. Splitting a logic program. In Logic Programming, Proceedings of the Eleventh International Conference on Logic Programming, P. V. Hentenryck (ed.), 23–37. MIT Press.Google Scholar
Lindström, P. 1966. First order predicate logic with generalized quantifiers. Theoria, Wiley Online Library 32(3), 186195.Google Scholar
Lloyd, J. W. 1987. Foundations of Logic Programming, 2nd Edition. Springer.Google Scholar
Maes, P. 1991. The agent network architecture (ANA). SIGART Bulletin 2(4), 115120.Google Scholar
Maes, P. 1993. Modeling adaptive autonomous agents. Artificial Life 1(1–2), 135162.Google Scholar
Mancarella, P. & Pedreschi, D. 1988. An algebra of logic programs. In Logic Programming, Proceedings of the Fifth International Conference and Symposium, 1006–1023. MIT Press.Google Scholar
Manna, M., Scarcello, F. & Leone, N. 2011. On the complexity of regular-grammars with integer attributes. Journal of Computer and System Sciences 77(2), 393421.Google Scholar
Maratea, M., Pulina, L. & Ricca, F. 2015. Multi-level algorithm selection for ASP. In Proceedings of the Logic Programming and Nonmonotonic Reasoning - 13th International Conference, LPNMR 2015, Lecture Notes in Computer Science 9345, 439–445. Springer.Google Scholar
Marek, V. W. & Truszczyński, M. 1999. Stable models and an alternative logic programming paradigm. In The Logic Programming Paradigm, 375–398. Springer.Google Scholar
Mascardi, V., Demergasso, D. & Ancona, D. 2005. Languages for programming BDI-style agents: an overview. In WOA 2005: Dagli Oggetti agli Agenti. 6th AI*IA/TABOO Joint Workshop “From Objects to Agents”: Simulation and Formal Analysis of Complex Systems, F. D. Paoli, E. Merelli and A. Omicini (eds), 9–15. Pitagora Editrice Bologna.Google Scholar
Mascardi, V., Martelli, M. & Sterling, L. 2004. Logic-based specification languages for intelligent software agents. Theory and Practice of Logic Programming 4(4), 429494.Google Scholar
Meyer, B. 1990. Introduction to the Theory of Programming Languages. Prentice Hall.Google Scholar
Meyer, D. E. & Kieras, D. E. 1997. A computational theory of executive cognitive processes and multiple-task performance: part I. basic mechanisms. Psychological Review 104(1), 3.Google Scholar
Miller, D. 1986. A theory of modules for logic programming. In SLP, 106–114. IEEE-CS.Google Scholar
Moore, R. C. 1985. Semantical considerations on nonmonotonic logic. Artificial Intelligence 25(1), 7594.Google Scholar
Mostowski, A. 1957. On a generalization of quantifiers. Fundamenta Mathematicae 44(1), 1236.Google Scholar
Müller, J. P. & Pischel, M. 1994. An architecture for dynamically interacting agents. International Journal of Cooperative Information Systems 3(1), 2546.Google Scholar
Nam, T. H. & Baral, C. 2009. Hypothesizing about signaling networks. Journal of Applied Logic 7(3), 253274.Google Scholar
Neches, R., Langley, P. & Klahr, D. 1987. Learning, Development, and Production Systems. The MIT Press.Google Scholar
Newell, A. 1973. Production systems: models of control structures. In Visual Information Processing, 463–526. Elsevier.Google Scholar
Newell, A. 1990. Unified Theories of Cognition. Harvard University Press.Google Scholar
Niemelä, I. 1999. Logic programs with stable model semantics as a constraint programming paradigm. Annals of Mathematics and Artificial Intelligence 25(3–4), 241273.Google Scholar
Nogueira, M., Balduccini, M., Gelfond, M., Watson, R. & Barry, M. 2001. An A prolog decision support system for the space shuttle. In Answer Set Programming, Towards Efficient and Scalable Knowledge Representation and Reasoning, Proceedings of the 1st Intl. ASP’01 Workshop, A. Provetti and T. C. Son (eds).Google Scholar
Novák, P. 2008. An Open Agent Architecture: Fundamentals. Technical Report No. IfI-07-10, Department of Informatics, Clausthal University of Technology (November 2007).Google Scholar
Novák, P. 2009. Jazzyk: a programming language for hybrid agents with heterogeneous knowledge representations. In Programming Multi-Agent Systems, 6th International Workshop, ProMAS 2008. Revised Invited and Selected Papers, K. V. Hindriks, A. Pokahr and S. Sardiña (eds), Lecture Notes in Computer Science 5442, 72–87. Springer.Google Scholar
Novák, P. & Dix, J. 2008. Adding structure to agent programming languages. In Programming Multi-Agent Systems, 5th International Workshop, ProMAS 2007, Honolulu, HI, USA, May 15, 2007, Revised and Invited Papers, M. Dastani, A. E. Fallah-Seghrouchni, A. Ricci and M. Winikoff (eds), Lecture Notes in Computer Science 4908, 140–155. Springer.Google Scholar
Oikarinen, E. 2008. Modularity in Answer Set Programs. PhD thesis, Helsinki University of Technology.Google Scholar
O’Keefe, R. A. 1985. Towards an algebra for constructing logic programs. In Proceedings of the 1985 Symposium on Logic Programming, 152–160. IEEE-CS.Google Scholar
Omicini, A. 2001. SODA: societies and infrastructures in the analysis and design of agent-based systems. In Agent-Oriented Software Engineering, First International Workshop, AOSE 2000, Revised Papers, P. Ciancarini and M. Wooldridge (eds), Lecture Notes in Computer Science 1957, 185–193. Springer.Google Scholar
Osorio, M., Zepeda, C., Nieves, J. C. & Cortés, U. 2005. Inferring acceptable arguments with answer set programming. In Sixth Mexican International Conference on Computer Science (ENC) 2005), I198–205. EEE Computer Society.Google Scholar
Petrie, C. J. 1996. Agent-based engineering, the web, and intelligence. IEEE Expert 11(6), 2429.Google Scholar
Pokahr, A., Braubach, L. & Lamersdorf, W. 2005. Jadex: a BDI reasoning engine. In Multi-Agent Programming: Languages, Platforms and Applications, R. H. Bordini, M. Dastani, J. Dix and A. E. Fallah-Seghrouchni (eds), Multiagent Systems, Artificial Societies, and Simulated Organizations 15, 149–174. Springer.Google Scholar
Przymusinski, T. C. 1988. On the declarative semantics of deductive databases and logic programs. In Foundations of Deductive Databases and Logic Programming, 193–216. Morgan Kaufmann.Google Scholar
Pylyshyn, Z. W. 1990. Computation and Cognition. Bradford/MIT Press.Google Scholar
Rao, A. S. 1996. AgentSpeak (L): BDI agents speak out in a logical computable language. In Agents Breaking Away, 7th European Workshop on Modelling Autonomous Agents in a Multi-Agent World, Proceedings, 42–55. Springer.Google Scholar
Rao, A. S. & Georgeff, M. 1991. Modeling rational agents within a BDI-architecture. In Proceedings of the Second International Conference on Principles of Knowledge Representation and Reasoning (KR’91), 473–484. Morgan Kaufmann.Google Scholar
Rao, A. S. & Georgeff, M. 1995. BDI agents: from theory to practice. in Proceedings of the First International Conference on Multiagent Systems ICMAS95, V. R. Lesser and L. Gasser (eds), 312–319. The MIT Press.Google Scholar
Reiter, R. 1980. A logic for default reasoning. Artificial intelligence 13(1), 81132.Google Scholar
Ricca, F. 2003. The DLV java wrapper. In APPIA-GULP-PRODE, 263–274. Citeseer.Google Scholar
Ricca, F., Dimasi, A., Grasso, G., Ielpa, S. M., Iiritano, S., Manna, M. & Leone, N. 2010. A logic-based system for e-tourism. Fundamenta Informaticae 105(1–2), 3555.Google Scholar
Ricca, F., Grasso, G., Alviano, M., Manna, M., Lio, V., Iiritano, S. & Leone, N. 2012. Team-building with answer set programming in the Gioia-Tauro seaport. Theory and Practice of Logic Programming 12(3), 361381.Google Scholar
Ricci, A., Viroli, M. & Omicini, A. 2007. CArtAgO: a framework for prototyping artifact-based environments in MAS. In Environments for Multi-Agent Systems III, Third International Workshop, E4MAS 2006, Selected Revised and Invited Papers, D. Weyns, H. Van Dyke Parunak and F. Michel (eds), LNCS 4389, 67–86. Springer.Google Scholar
Rogers, T. J., Ross, R. & Subrahmanian, V. 2000. Impact: a system for building agent applications. Journal of Intelligent Information Systems 14(2–3), 95113.Google Scholar
R.Thomas, S. 1993. PLACA, An Agent Oriented Programming Language. PhD thesis, Computer Science Department, Stanford University. Available as Technical Report STAN-CS-93-1487.Google Scholar
Samsonovich, A. V. 2010. Toward a unified catalog of implemented cognitive architectures. BICA 221, 195244.Google Scholar
Shardlow, N. 1990. Action and Agency in Cognitive Science, Master’s thesis, Department of Psycology, University of Manchester.Google Scholar
Shoham, Y. 1993. Agent-oriented programming. Artificial Intelligence 60(1), 5192.Google Scholar
Sloman, A. & Logan, B. 1998. Architectures and tools for human-like agents. In Proceedings of the 2nd European Conference on Cognitive Modelling, 58, 65. University of Nottingham Press.Google Scholar
SOAR-Research-Group 2010. SOAR: a comparison with rule-based systems. http://sitemaker.umich.edu/soar/home Google Scholar
Son, T. C., Pontelli, E., Gelfond, M. & Balduccini, M. 2016. An answer set programming framework for reasoning about truthfulness of statements by agents. In Technical Communications of the 32nd International Conference on Logic Programming, ICLP 2016, OASICS 52, 8:1–8:4. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik.Google Scholar
Sridharan, M. 2016. Towards an architecture for representation, reasoning and learning in human-robot collaboration. In 2016 AAAI Spring Symposium Series.Google Scholar
Tari, L., Baral, C. & Anwar, S. 2005. A language for modular answer set programming: application to ACC tournament scheduling. In Answer Set Programming, Advances in Theory and Implementation, Proceedings of the 3rd International ASP’05 Workshop, CEUR Workshop Proceedings 142, CEUR-WS.org.Google Scholar
Tiihonen, J., Soininen, T., Niemelä, I. & Sulonen, R. 2003. A practical tool for mass-customising configurable products. In DS 31: Proceedings of ICED 03, the 14th International Conference on Engineering Design.Google Scholar
Togelius, J. 2003. Evolution of the Layers in a Subsumption Architecture Robot Controller, Master’s thesis, University of Sussex.Google Scholar
Torroni, P. 2004. Computational logic in multi-agent systems: recent advances and future directions. Annals of Mathematics and Artificial Intelligence 42(1–3), 293305.Google Scholar
Truszczyński, M. 2007. Logic programming for knowledge representation. In Logic Programming, 76–88. Springer.Google Scholar
Van Nieuwenborgh, D., De Vos, M., Heymans, S. & Vermeir, D. 2006. Hierarchical decision making in multi-agent systems using answer set programming. In Computational Logic in Multi-Agent Systems, 20–40. Springer.Google Scholar
van Riemsdijk, M. B., Dastani, M., Meyer, J.-J. C. & de Boer, F. S. 2006. Goal-oriented modularity in agent programming. In 5th International Joint Conference on Autonomous Agents and Multiagent Systems AAMAS 2006, 1271–1278. ACM Press.Google Scholar
Vere, S. & Bickmore, T. 1990. A basic agent. Computational Intelligence 6(1), 4160.Google Scholar
Wood, M. F. & DeLoach, S. A. 2001. An overview of the multiagent systems engineering methodology. In Agent-Oriented Software Engineering, First International Workshop, AOSE 2000, Revised Papers, P. Ciancarini and M. Wooldridge (eds), Lecture Notes in Computer Science 1957, 207–222. Springer.Google Scholar
Wood, S. 1993. Planning and Decision-Making in Dynamic Domains. Ellis Horwood Series in Artificial Intelligence.Google Scholar
Wooldridge, M. 1997. Agent-based software engineering. IEEE Proceedings on Software Engineering 144(1), 2637.Google Scholar
Wooldridge, M. 1999. Multiagent systems. In Multiagent Systems, G. Weiss, (ed.), chapter on Intelligent Agents, 27–77. MIT Press. http://dl.acm.org/citation.cfm?id=305606.305607 Google Scholar
Wooldridge, M. J. 2000. Reasoning About Rational Agents. MIT Press.Google Scholar
Wooldridge, M. & Jennings, N. R. 1994. Agent theories, architectures, and languages: a survey In Intelligent Agents, ECAI-94 Workshop on Agent Theories, Architectures, and Languages, Proceedings, 1–39. Springer.Google Scholar
Wooldridge, M., Jennings, N. R. & Kinny, D. 2000. The Gaia methodology for agent-oriented analysis and design. Autonomous Agents and Multi-Agent Systems 3(3), 285312.Google Scholar
Wooldridge, M. & Jennings, N. R. 1995. Intelligent agents: theory and practice. Knowledge Engineering Review 10(2), 115152.Google Scholar
Zhang, S., Sridharan, M. & Wyatt, J. L. 2015. Mixed logical inference and probabilistic planning for robots in unreliable worlds. IEEE Transaction on Robotics 31(3), 699713.Google Scholar