Ontology negotiation between intelligent information agents

Abstract

This paper describes an approach to ontology negotiation between agents supporting intelligent information management. Ontologies are declarative (data-driven) expressions of an agent's "world": the objects, operations, facts and rules that constitute the logical space within which an agent performs. Ontology negotiation enables agents to cooperate in performing a task, even if they are based on different ontologies.Our objective is to increase the opportunities for "strange agents" -that is, agents not necessarily developed within the same framework or with the same contextual operating assumptions -to communicate in solving tasks when they encounter each other on the web. In particular, we have focused on information search tasks.We have developed a protocol that allows agents to discover ontology conflicts and then, through incremental interpretation, clarification and explanation, establish a common basis for communicating with each other. We have implemented this protocol in a set of Java classes that can be added to a variety of agents, irrespective of their underlying ontological assumptions. We have demonstrated the use of the protocol, through this implementation, in a test-bed that includes two large scientific archives: NASA's Global Change Master Directory and NOAA's Wind and Sea Index. This paper presents an overview of different methods for resolving ontology mismatches and motivates the Ontology Negotiation Protocol (ONP) as a method that addresses some problems with other approaches. Much remains to be done. The protocol must be tested in larger and less familiar contexts (for example, numerous archives that have not been preselected) and it must be extended to accommodate additional forms of clarification and ontology evolution.

Collaborative Learning of Ontology Fragments by Co-operating Agents

“…This is a comparable technique with the agent approaches of [5], [6], and [7], which learn a single concept at a time (see Section II). 3) Learn-everything approach: learns all axioms in all of the fragments it locates.…”

“…The approaches presented by Bailin and Truszkowski [5], Afsharchi et al [6], and Soh [7] enable agents to augment their ontologies with one new concept at a time. In particular, Bailin and Truszkowski's approach considers semantically equivalent representations by using WordNet [8] to translate concepts to aid communication between agents.…”

A Cooperative Approach for Composite Ontology Mapping

“…For the mapping between the terms "Music/History" and "Architecture/ History", each agent has as arguments AR = {1,2,3} and as relations of attack attacks = { (3,1), (3,2), (1,3), (2,3)}. These sets are generated by each agent, after receiving the arguments of the other agents.…”

“…The links between related concepts are the result of the preferred mappings of each agent, instead of an integrated ontology upon which the agents will be able to communicate for a specific purpose. We do not consider negotiation steps such as the ones presented in [1], namely clarification and explanation. But we consider different mapping methods represented by different audiences selecting by argumentation the best solution for the mapping problem.…”

An Extended Value-Based Argumentation Framework for Ontology Mapping with Confidence Degrees

“…For the mapping between the terms "Music/History" and "Architecture/ History", each agent has as arguments AR = {1,2,3} and as relations of attack attacks = { (3,1), (3,2), (1,3), (2,3)}. These sets are generated by each agent, after receiving the arguments of other agents.…”