Abstract
We propose an approach for modelling, integrating, and querying distributed probabilistic contexts in multi-agent systems. We assume each agent to be equipped with an independently acquired uncertain context. By taking advantage of established database technologies, we represent the uncertain context of each agent as a set of probabilistic facts conveniently stored in a probabilistic database. Members of a multi-agent system act autonomously and interact with each other. The interaction between agents consists of sharing access to their contexts with each other and allowing queries over the combined shared contexts. This amounts to the challenge of combining and querying distributed probabilistic databases. To combine probabilistic contexts, we define a context-matching operator that creates a joint probability distribution with given marginal probabilities. Furthermore, we propose a query answering method over combinations of probabilistic contexts.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Menger, K.: Random variables from the point of view of a general theory of variables. In: Proceedings of the 3rd Berkeley Symposium on Mathematical Statistics and Probability, Volume 2: Contributions to Probability Theory, pp. 215–229 (1956)
Suciu, D., Olteanu, D., Ré, C., Koch, C.: Probabilistic Databases. Morgan & Claypool, San Rafael (2011)
Fréchet, M.: Sur les tableaux de corrélation dont les marges sont donnés. Annales de l’Université de Lyon 4, 53–57 (1951)
Morgensten, D.: Einfache Beispiele zweidimensionaler Verteilungen. Mitteilungsblatt fuer mathematische Statistik 8, 234–235 (1959)
Sklar, A.: Fonctions de répartition à n dimensions et leur marges. Publication Statistical Institute de l’Université de Paris 8, 229–231 (1959)
Genest, C., Neslehova, J.: A primer on copulas for count data. ASTIN Bul. J. IAA 37(2), 475–515 (2007)
van den Broeck, G., Suciu, D.: Query processing on probabilistic data: a survey. Found. Trends Databases 7(3–4), 197–341 (2017)
Rode, S., Turner, R.M.: Representing and communicating context in multiagent systems. In: Christiansen, H., Stojanovic, I., Papadopoulos, G.A. (eds.) CONTEXT 2015. LNCS (LNAI), vol. 9405, pp. 257–270. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-25591-0_19
Garant, D., da Silva, B.C., Lesser, V., Zhang, C.: Context-based concurrent experience sharing in multiagent systems. In: Proceedings of AAMAS 2017, pp. 1544–1546 (2017)
Dorri, A., Kanhere, S.S., Jurdak, R.: Multi-agent systems: a survey. IEEE Access 6, 28573–28593 (2018)
Chen, F., Ren, W.: On the control of multi-agent systems: a survey. Found. Trends Syst. Control 6(4), 339–499 (2019)
Furche, T., et al.: DIADEM: thousands of websites to a single database. PVLDB 7(14), 1845–1856 (2014)
Govindaraju, V., Zhang, C., Ré, C.: Understanding tables in context using standard NLP toolkits. In: Proceedings of ACL 2013, pp. 658–664 (2013)
Zhang, C., Shin, J., Ré, C., Cafarella, M., Nui, F.: Extracting databases from dark data with DeepDive. In: Proceedings of SIGMOD 2016, pp. 847–859 (2016)
Zhang, C., Ré, C., Cafarella, M.J., Shin, J., Wang, F., Wu, S.: DeepDive: declarative knowledge base construction. Commun. ACM 60(5), 93–102 (2017)
Nelson, R.B.: An Introduction to Copulas. Springer Series in Statistics, 2nd edn. Springer, New York (2006). https://doi.org/10.1007/0-387-28678-0
Bellahsene, Z., Bonifati, A., Rahm, E. (eds.): Schema Matching and Mapping. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-16518-4
Das Sarma, A., Dong, X.L., Halevy, A.Y.: Uncertainty in data integration and dataspace support platforms. In: Bellahsene, Z., Bonifati, A., Rahm, E. (eds.) Schema Matching and Mapping. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-16518-4_4
Fagin, R., Kolaitis, P.G., Miller, R.J., Popa, L.: Data exchange: semantics and query answering. Theor. Comput. Sci. 336(1), 89–124 (2005)
Fagin, R., Kimelfeld, B., Kolaitis, P.G.: Probabilistic data exchange. J. ACM 58(4), 1–55 (2011)
Lukasiewicz, T., Martinez, M.V., Predoiu, L., Simari, G.I.: Existential rules and Bayesian networks for probabilistic ontological data exchange. In: Bassiliades, N., Gottlob, G., Sadri, F., Paschke, A., Roman, D. (eds.) RuleML 2015. LNCS, vol. 9202, pp. 294–310. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-21542-6_19
Lukasiewicz, T., Martinez, M.V., Predoiu, L., Simari, G.I.: Basic probabilistic ontological data exchange with existential rules. In: Proceedings of AAAI 2016, pp. 1023–1029 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Predoiu, L. (2019). Combining Probabilistic Contexts in Multi-Agent Systems. In: Bella, G., Bouquet, P. (eds) Modeling and Using Context. CONTEXT 2019. Lecture Notes in Computer Science(), vol 11939. Springer, Cham. https://doi.org/10.1007/978-3-030-34974-5_17
Download citation
DOI: https://doi.org/10.1007/978-3-030-34974-5_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-34973-8
Online ISBN: 978-3-030-34974-5
eBook Packages: Computer ScienceComputer Science (R0)