Abstract
This paper introduces the agent platform HumanSim, a combination of the BDI-paradigm and Answer Set Programming (ASP), to simulate entities in three-dimensional virtual environments. We show how ASP can be used to (i) annotate a virtual three-dimensional world and (ii) to model the goal selection behavior of a BDI agent. Using this approach it is possible to model the agent domain and its behavior – reactive or foresighted – with ASP. To demonstrate the practical use of HumanSim, we present a three-dimensional planning and simulation application, in which worker agents are driven by HumanSim in the shop floor domain. Furthermore, we show the results of an evaluation of HumanSim in the former mentioned simulation application.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
RAMSIS Automotive http://www.human-solutions.com/.
- 2.
FlexSim Simulation Software, https://www.flexsim.com/flexsim/.
- 3.
Web Ontology Language, http://www.w3.org/TR/owl2-overview/.
- 4.
Resource Description Framework, https://www.w3.org/RDF/.
- 5.
For a discussion of the problems involved in derived predicates in PDDL cf. [11].
- 6.
“Elaboration tolerance is the ability to accept changes to a person’s or a computer program’s representation of facts about a subject without having to start all over.” [12].
- 7.
Example of an engine which supports both tasks is unity3d: http://unity3d.com/.
- 8.
DEC ASP Rules: http://reasoning.eas.asu.edu/ecasp/examples/foundations/DEC.lp.
- 9.
Arguably, in 3D environments considered in the context of this paper, the closed world assumption is more appropriate.
- 10.
COMPASS (Collaborative Modular Prototyping And Simulation Server): https://github.com/dfki-asr/compass.
- 11.
FiVES (Flexible Virtual Environment Server): https://github.com/fives-team.
- 12.
To minimize the output of the ASP module, we use gringo filter statements #show.
- 13.
Jason: http://jason.sourceforge.net/.
References
Nesbigall, S., Warwas, S., Kapahnke, P., Schubotz, R., Klusch, M., Fischer, K., Slusallek, P.: ISReal: a platform for intelligent simulated realities. In: Filipe, J., Fred, A., Sharp, B. (eds.) ICAART 2010. CCIS, vol. 129, pp. 201–213. Springer, Heidelberg (2011)
Davies, N.P., Mehdi, Q.: BDI for intelligent agents in computer games. In: Proceedings of CGAMES 2006, The University of Wolverhampton (2006)
Bratman, M.E.: Intentions, Plans, and Practical Reasoning. Cambridge University Press, Cambridge (1999)
Busetta, P., Ronnquist, R., Hodgson, A., Lucas, A.: JACK Intelligent Agents - Components for Intelligent Agents in Java (1999)
Pokahr, A., Braubach, L., Lamersdorf, W.: Jadex: a BDI reasoning engine. In: Bordini, R.H., Dastani, M., Dix, J., Seghrouchni, A.E.F. (eds.) Multi-Agent Programming: Languages, Platforms and Applications. Multiagent Systems, Artificial Societies, and Simulated Organizations, vol. 15, pp. 149–174. Springer, New York (2005)
Radkowski, R., Huck, W., Domik, G., Holtmann, M.: Serious games for the therapy of the posttraumatic stress disorder of children and adolescents. In: Shumaker, R. (ed.) Virtual and Mixed Reality, Part II, HCII 2011. LNCS, vol. 6774, pp. 44–53. Springer, Heidelberg (2011)
Gelfond, M., Lifschitz, V.: The stable model semantics for logic programming. In: 5th International Conference on Logic Programming (ICLP), pp. 1070–1080. MIT Press, Cambridge (1988)
Lifschitz, V.: What Is Answer Set Programming? Department of Computer Sciences, University of Texas at Austin (2008)
Brain, M., De Vos, M.: Answer set programming a domain in need of explanation. In: Proceeding of 3rd International Workshop on Explanation-aware Computing (ExaCat), pp. 391–403. CEUR-WS.org (2008)
Mueller, E.T.: Commonsense Reasoning. Elsevier Science, Amsterdam (2006)
Thiebaux, S., Hoffmann, J., Nebel, B.: In defense of PDDL axioms. Artif. Intell. 168(1–2), 38–69 (2005)
McCarthy, J.: Elaboration Tolerance. Common-Sense 98 (1998)
Gelfond, M.: Answer sets. In: van Harmelen, F., Lifschitz, V., Porter, B. (eds.) Handbook of Knowledge Representation. Elsevier, Amsterdam (2007)
Simons, P., Niemela, I., Soininen, T.: Extending and implementing the stable model semantics. Artif. Intell. J. 138, 181–234 (2002)
Lee, J., Palla, R.: Reformulating the situation calculus and the event calculus inthe general theory of stable models and in answer set programming. J. Artif. Intell. Res. 43, 571–620 (2012)
Lee, J.H., Li, T., De Vos, M., Padget, J.: Using social institutions to guide virtual agent behaviour. In: The AAMAS Workshop on Cognitive Agents for Virtual Environments (CAVE-2013) (2013)
Ryuh, Y.S., Moon, J.I.: Multi-agent control and implementation of bio-inspired underwater robots for mariculture monitoring and control. In: Robotics and Biomimetics, pp. 777–783. IEEE (2012)
Barenji, R.V., Barenji, A.V., Hashemipour, M.: A multi-agent RFID-enabled distributed control system for a flexible manufacturing shop. Int. J. Adv. Manuf. Technol. 71, 1773–1791 (2014)
Rao, A.S.: AgentSpeak(L): BDI agents speak out in a logical computable language. In: Perram, J., Van de Velde, W. (eds.) MAAMAW 1996. LNCS, vol. 1038. Springer, Heidelberg (1996)
Dastani, M., van Riemsdijk, M.B., Dignum, F.P.M., Meyer, J.-J.C.: A programming language for cognitive agents goal directed 3APL. In: Dastani, M., Dix, J., El Fallah-Seghrouchni, A. (eds.) PROMAS 2003. LNCS (LNAI), vol. 3067, pp. 111–130. Springer, Heidelberg (2004)
Constantini, S., Tocchio, A.: DALI: An architecture for intelligent logical agents. In: Proceedings of International Workshop on Architectures for Intelligent Theory-Based Agents (AITA 2008), AAAI (2008)
Krümpelmann, P., Thimm, M., Ritterskamp, M., Kern-Isberner, G.: Belief operations for motivated BDI agents. In: Proceedings of Autonomous Agents and Multiagent Systems (AAMAS 2008), pp. 421–428 (2008)
Costantini, S.: Answer set modules for logical agents. In: de Moor, O., Gottlob, G., Furche, T., Sellers, A. (eds.) Datalog 2010. LNCS, vol. 6702, pp. 37–58. Springer, Heidelberg (2011)
Walczak, A., Braubach, L., Pokahr, A., Lamersdorf, W.: Augmenting BDI agents with deliberative planning techniques. In: Bordini, R.H., Dastani, M., Dix, J., Fallah Seghrouchni, A. (eds.) PROMAS 2006. LNCS (LNAI), vol. 4411, pp. 113–127. Springer, Heidelberg (2007)
de Silva, L., Sardina, S., Padgham, L.: First principles planning in BDI systems. In: Proceedings of Autonomous Agents and Multi-Agent Systems (AAMAS), vol. 2, pp. 1001–1008 (2009)
Sardina, S., Padgham, L.: A BDI agent programming language with failure recovery, declarative goals, and planning. In: Proceedings of Autonomous Agents and Multi-Agent Systems (AAMAS 2011), vol. 23, pp. 18–70 (2011)
Müller, J.P., Pischel, M.: The Agent Architecture InteRRaP: Concept and Application. Research Report RR-93-26, German Artificial Intelligence Research Center (DFKI), Saarbrcken, June 1993
Acknowledgments
The research described in this paper has been funded by the German Federal Ministry of Education and Research (BMBF) through the projects Collaborate3D and INVERSIV.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Antakli, A., Zinnikus, I., Klusch, M. (2016). ASP-Driven BDI-Planning Agents in Virtual 3D Environments. In: Klusch, M., Unland, R., Shehory, O., Pokahr, A., Ahrndt, S. (eds) Multiagent System Technologies. MATES 2016. Lecture Notes in Computer Science(), vol 9872. Springer, Cham. https://doi.org/10.1007/978-3-319-45889-2_15
Download citation
DOI: https://doi.org/10.1007/978-3-319-45889-2_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-45888-5
Online ISBN: 978-3-319-45889-2
eBook Packages: Computer ScienceComputer Science (R0)