Stanislav Ustymenko

Ontology-supported sharing and reuse of knowledge in diverse environments

In this paper, we discuss the use of ontologies to improve knowledge sharing and reuse.

Dynamic agent-oriented reasoning about belief and trust

The newly envisioned Semantic Web contains as a component what may be called a Web of Trust, consisting of the trust relationships held between its participants. In terms of this, the degree to which participant A believes what is believed by participant B depends on the degree to which A trusts B. This paper presents a formal language with well-defined semantics within which such a participant (or agent) can express the relevant conditions of belief and trust, and outlines some key techniques for reasoning with these expressions. Novel in this treatment is the use of linguistic, rather than numeric, measures of belief. The aim in this is to make the language and reasoning system more intuitive for the human user. Also novel is an explicit delineation of the context within which the language and reasoning techniques are to be applied. The notion of a dynamic reasoning system is applied to model the agents knowledge acquisition and belief revision processes as activities that take place in time.

Modeling local belief revision in a dynamic reasoning system

The well-known AGM framework provides an intuitively plausible model of nonmonotonic belief revision, but it has the drawback that it is not computational. A computational variant has been proposed by Hansson, and subsequently Hansson and Wassermann have identified a notion of local belief change and discussed how this can modeled in an adaptation of Hansson framework. Briefly, the belief set is compartmentalized in such a way that consistency may be preserved in one compartment, while inconsistency may be entertained in another compartment without the entire belief system degenerating to the trivial case where all propositions are believed. An alternative to the AGM framework is the Dynamic Reasoning System (DRS), which models reasoning explicitly as a temporal activity. The objective in this paper is to show how the phenomenon of local belief change studied by Hansson and Wassermann can be modeled in the DRS framework.

Algorithms for Maintaining a Consistent Knowledge Base in Distributed Multiagent Environments

In this paper, we design algorithms for a system that allows Semantic Web agents to reason within what has come to be known as the Web of Trust. We integrate reasoning about belief and trust, so agents can reason about information from different sources and deal with contradictions. Software agents interact to support users who publish, share and search for documents in a distributed repository. Each agent maintains an individualized topic taxonomy for the user it represents, updating it with information obtained from other agents. Additionally, an agent maintains and updates trust relationships with other agents.

Dynamic reasoning for description logic terminologies

The Semantic Web presents the challenge of designing agents capable of continuously updating their knowledge bases Semantic Web ontologies are commonly represented using description logic knowledge bases We demonstrate description logic reasoning using a Dynamic Reasoning System (DRS) This explicitly portrays reasoning as a process taking place in time and allows for manipulating inconsistent knowledge bases.

Architecture for Belief Revision in Multi-Agent Intelligent Systems

The Semantic Web provides a framework for agents to easily publish and consume structured knowledge suitable for automatic reasoning. However, the open and distributed nature of the Web causes information of dubious quality to be published by sinister or incompetent agents. At the same time, Web accessible knowledge can change often. As a result, agents are forced to function in an environment of unreliable, incomplete, and contradictory information. They require mechanisms to change their beliefs dynamically and remove contradictions while maintaining the quality of the knowledge base. Computational agents might rely on social networks to judge information quality. Relationships of trust help determine the degree of belief an agent may ascribe to a given proposition. A previous work has proposed a formal logic for agent-oriented reasoning about belief and trust. This logic allows agents to deduce their confidence levels on both received and inferred knowledge. The present paper shows how to employ this logic in a collaborative document repository for scientific literature. Such a system relies on user-supplied classification data to construct comprehensive, personalized taxonomies for document browsing and search. It is based on a system of multiple agents representing users, constantly involved in knowledge acquisition and belief revision to provide the users with the best data available. The paper describes the theoretical foundations and briefly outlines a software implementation.

Trust and classification: towards community ontology revision and knowledge management

This paper explores theoretical and practical approaches to knowledge management. We show how ontologies and communities of practice can be used to create a distributed knowledge repository and how a classic Belief Revision framework is essential in this environment.

Architecture for Decision‐Making and Task‐Oriented Reasoning for the Web of Trust

This paper presents an architecture for a system that allows Semantic Web agents to reason within what has come to be known as the Web of Trust. We integrated reasoning about belief and trust, so agents can reason about information from different sources and deal with contradictions. Software agents interact to support users who publish, share and search for documents in a distributed repository. Each agent maintains an individualized topic taxonomy for the user it represents, updating it with information obtained from other agents. When new information leads to a contradiction, the agent performs a belief revision process informed by a degree of belief in a statement and a degree of trust an agent has for the information source.

An Agent-Oriented Logic for Belief and Trust

The newly envisioned semantic Web contains as a component what may be called a Web of Trust, consisting of the trust relationships held between its participants. In terms of this, the degree to which participant A believes what is believed by participant B depends on the degree to which A trusts B. This paper presents a formal language with well-defined semantics within which such a participant (or agent) can express the relevant conditions of belief and trust, and outlines some key techniques for reasoning with these expressions. Novel in this treatment is the use of linguistic, rather than numeric, measures of belief. The aim in this is to make the language and reasoning system more intuitive for the human user. Also novel is an explicit delineation of the context within which the language and reasoning techniques are to be applied

On merging user-supplied topic ontologies on the semantic web

The Semantic Web [2] is a vision of a new generation of the WWW that will enable computational agents to process data that have well-defined formal semantics. Agents can use reasoning to infer new information from statements located on different Web sites. Just like the current WWW, the Semantic Web makes no attempt to centralize publishing, effectively allowing anyone to publish any statement. Thus judging reliability of information becomes a practical requirement.