Abstract
Pervasive environments become a reality and involve a large variety of networking smart devices. This ambient intelligence tends to complex interactions. Lots of researches have been done on intelligent and reactive architectures able to manage multiple events and act in the environment. In the Robotics domain, a decision process must be implemented in the robot brain or a collective intelligence to accomplish the multimodal interaction with humans in human environment. We present a semantic agents architecture giving the robot and other entities the ability to well understand what is happening and thus provide more robust processing. We will describe our agent memory. Intelligence and knowledge about objects in the environment is stored in two ontologies linked to a reasoner an inference engine. To share and exchange information, an event knowledge representation language is used by semantic agents. This pervasive architecture brings other advantages: cooperation, redundancy, adaptability, interoperability and platforms independent.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Guarino, N.: Formal ontology, conceptual analysis and knowledge representation. Human-Computer Studies 43(5/6), 625–640 (1995)
Leo, O.: Ontologies for semantically Interoperable Systems. In: Proceedings of the Twelfth International Conference on Information and Knowledge Management, New Orleans, LA, USA, pp. 366–369. ACM Press, New York (2003)
Macal Charles, M., North Michael, J.: Tutorial on agent-based modeling and simulation part 2: How to model with agents. In: Perrone, L.F., Wieland, F.P., Liu, J., Lawson, B.G., Nicol, D.M., Fujimoto, R.M. (eds.) Proceedings of the 2006 Winter Simulation Conference (2006)
Allan, R.: Survey of Agent Based Modeling and Simulation Tools. Technical Report (2009), http://epubs.cclrc.ac.uk/work-details?w=50398
Erik, B., Ivan, K., John, S., Kokar, M.M., Subrata, D., Powell, G.M., Orkill, D.D., Ruspini, E.H.: Issues and Challenges in Situation Assessment (Level 2 Fusion). Journal of Advances in Information Fusion 1(2) (December 2006)
Michael, J., Paolo, B., Burnett Daniel, C., Jerry, C., Dahl Deborah, A.: MacCobb Gerry and Ragget Dave: EMMA: Extensible MultiModal Annotation markup language. W3C Recommendation (February 2009)
Kranstedt, A., Kopp, S., Wachsmuth, I.: Murml: A multimodal utterance representation markup language for conversational agents. In: Proc. of the AAMAS, Workshop on Embodied conversational agents - Let’s specify and evaluate them (2002)
Frédéric, L., Denis, A., Ricci, A., Romary, L.: Multimodal meaning representation for generic dialogue systems architectures. In: Proc. on Language Resources and Evaluation (LREC 2004), pp. 521–524 (2004)
Manuel, G., Alois, K.: MultiML - A General Purpose Representation Language for Multimodal Human Utterances. In: ICMI 2008, Chania, Crete, Greece (2008)
Mark, S., Jason, B.: Combinatory Categorial Grammar to appear. In: Borsley, R., Borjars, K. (eds.) Non-Transformational Syntax. Blackwell, Malden (2005)
Jun-young, K., Ji Young, Y., Shinn Richard H.: An Intelligent Robot Architecture based on Robot Mark-up Languages. In: Proceedings of IEEE International Conference on Engineering of Intelligent Systems (ICEIS), pp. 1–6 (2006)
Piero, Z.G.: Representation and Processing of Complex Events. In: Association for the Advancement of Artificial Intelligence AAAI Spring Symposium (2009)
Marvin, M.: Matter, Mind and Models. In: Proceedings of IFIP Congress, Spartan Books, Wash. D.C, pp. 45–49 (1965); Reprinted in Semantic Information Processing. A short paper proposing a theory of self-knowledge and the illusion of free will (1965)
Quillian Ross Semantic memory.: Ph.D. thesis, Carnegie Intstitute of Technology (1966); Minsky, M. (ed.) Semantic Information Processing, p. 262. MIT Press, Cambridge (1968)
Michael, J.: Building Multimodal Applications with EMMA. In: ICMI-MLMI 2009, November 2-4. ACM, Cambridge (2009), 978-1-60558-772-1/09/11
Frédéric, L.: Physical, semantic and pragmatics levels for multimodal fusion and fission. In: Seventh International Workshop on Computational Semantics (IWCS-7), Tilburg, The Netherlands, pp. 346–350 (2007)
Bolt, R.: “Put That Here”: Voice and gesture at the graphics interface. In: Proceedings of the 7th Annual Conference on Computer Graphics and Interactive Techniques (1980)
SOAP website, http://www.w3.org/TR/soap12-part0
OWL website, http://www.w3.org/TR/owl-features/
KAON website, http://kaon2.semanticweb.org
Pellet website, http://clarkparsia.com/pellet
JESS website, http://www.jessrules.com
FACT++ website, http://owl.man.ac.uk/factplusplus/
EMMA website, http://www.w3.org/TR/emma
FIPA website, http://www.fipa.org
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dourlens, S., Ramdane-Cherif, A. (2010). Semantic Memory for Pervasive Architecture. In: Zhu, R., Zhang, Y., Liu, B., Liu, C. (eds) Information Computing and Applications. ICICA 2010. Lecture Notes in Computer Science, vol 6377. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16167-4_13
Download citation
DOI: https://doi.org/10.1007/978-3-642-16167-4_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16166-7
Online ISBN: 978-3-642-16167-4
eBook Packages: Computer ScienceComputer Science (R0)