MOSIG Master 2ND YEAR Research
YEAR 2017/2018

Ontology features influencing alignment evolution

Master topic / Sujet de master recherche

Ontologies are formal representations of entities that can be found in the world. Alignments allows agents to communicate by relating these ontologies together. Agents may need to repair and evolve their alignments as soon as they cause communication failures. We aim at better understanding which factors (ontology size, environment complexity, ontology distribution across agents) influence this evolution.

We approach this problem through the framework of cultural evolution: Experimental cultural evolution provides a population of agents with interaction games that are played randomly. In reaction to the outcome of such games, agents adapt their knowledge. It is possible to test hypotheses by precisely crafting the rules used by agents in games and observing the consequences.

The cultural language evolution approach [Steels, 2012] has been applied to the evolution of the way agents represent knowledge [Euzenat, 2014; Anslow & Rovatsos, 2015; Chocron & Schorlemmer, 2016]. We have applied this approach to ontology alignment repair, i.e., the improvement of incorrect alignments [Euzenat, 2014; 2017a; b]. For that purpose, we performed a series of experiments in which agents react to mistakes in ontology alignments, expressing relations across ontology concepts [Euzenat & Shvaiko, 2013]. Agents only know about their ontologies and alignments with others and they act in a fully decentralised way. We showed that cultural repair is able to converge towards successful communication through improving the objective correctness of alignments.

However, such experiments were carried out with a relatively static society structure. The number of interacting agents was fixed and determined the complexity of the environment and the size of ontologies.

The goal of this master topic is to explore the influence of each of the above parameters on the cultural alignment repair process, i.e., on the resulting knowledge (level of coherence) and the process features (convergence speed). For that purpose, it will be necessary to design experimental protocols for testing variations of such features as the complexity of the environment (number of observed features), the completeness of the ontologies (number of represented features), the distribution of the used ontologies with respect to the full ontology space, or the number of agents using the same ontology. This last feature also introduces the opportunity to test how agents sharing the same ontology can develop independent alignments with the other ontologies and how such alignments may be explicitly synchronised.

Expected contributions are firstly the design of experimental scenarii adapted from those that we have already developed and the analysis of their results. They will be used to investigate, experimentally and/or theoretically, the influence of controlled factors and, hopefully, suggest new experiments.

This work is part of an ambitious program towards what we call cultural knowledge evolution and may prepare to a PhD.

References:

[Anslow & Rovatsos, 2015] Michael Anslow, Michael Rovatsos, Aligning experientially grounded ontologies using language games, Proc. 4th international workshop on graph structure for knowledge representation, Buenos Aires (AR), pp15-31, 2015 [DOI:10.1007/978-3-319-28702-7_2]
[Chocron & Schorlemmer, 2016] Paula Chocron, Marco Schorlemmer, Attuning ontology alignments to semantically heterogeneous multi-agent interactions, Proc. 22nd European Conference on Artificial Intelligence, Der Haague (NL), pp871-879, 2016 [DOI:10.3233/978-1-61499-672-9-871]
[Euzenat & Shvaiko, 2013] Jérôme Euzenat, Pavel Shvaiko, Ontology matching, 2nd edition, Springer-Verlag, Heildelberg (DE), 2013
[Euzenat, 2014] Jérôme Euzenat, First experiments in cultural alignment repair (extended version), in: Proc. 3rd ESWC workshop on Debugging ontologies and ontology mappings (WoDOOM), Hersounisos (GR), LNCS 8798:115-130, 2014 ftp://ftp.inrialpes.fr/pub/exmo/publications/euzenat2014c.pdf
[Euzenat, 2017a] Jérôme Euzenat, Communication-driven ontology alignment repair and expansion, in: Proc. 26th International joint conference on artificial intelligence (IJCAI), Melbourne (AU), pp185-191, 2017 ftp://ftp.inrialpes.fr/pub/moex/papers/euzenat2017a.pdf
[Euzenat, 2017b] Jérôme Euzenat, Crafting ontology alignments from scratch through agent communication, in: Proc. 20th International conference on principles and practive of multiagent systems (PRIMA), Nice (FR), pp245-262, 2017 ftp://ftp.inrialpes.fr/pub/moex/papers/euzenat2017b.pdf
[Steels, 2012] Luc Steels (ed.), Experiments in cultural language evolution, John Benjamins, Amsterdam (NL), 2012

Links:


Reference number: Proposal n°2373

Master profile: M2R MOSIG, Artificial intelligence and the web profile.

Advisor: Jérôme Euzenat (Jerome:Euzenat#inria:fr) and Manuel Atencia (Manuel:Atencia#inria:fr).

Team: The work will be carried out in the mOeX team common to INRIA & Université Grenoble Alpes. mOeX is dedicated to study knowledge evolution through adaptation. It gather permanent researchers from the Exmo team which has taken an active part these past 15 years in the development of the semantic web and more specifically ontology matching.

Laboratory: LIG.

Procedure: Contact us and provide vitæ, motivation letter and references.