Dynamic agent-oriented reasoning about belief and trust

2007

A serious problem on the WWW is finding reliable information. Not everything found on the Web is true and the Semantic Web does not change that in any way. The problem will be even more crucial for the Semantic Web, where agents will be integrating and using information from multiple sources. Thus, if an incorrect premise is used due to a single faulty source, then any conclusions drawn may be in error. Thus, statements published on the Semantic Web have to be seen as claims rather than as facts, and there should be a way to decide which among many possibly inconsistent sources is most reliable. In this work, we propose a trust model for the Semantic Web. The proposed model is inspired by the use trust in human society. Trust is a type of social knowledge and encodes evaluations about which agents can be taken as reliable sources of information or services. Our proposed model allows agents to decide which among different sources of information to trust and thus act rationally on the...

Proceedings of the 23rd International Conference on World Wide Web, 2014

Projects such as Libra and Cimple have built systems to capture knowledge in a research community and to respond to semantic queries. However, they lack the support for a knowledge base that can evolve over time while responding to queries requiring reasoning. We consider a semantic web that covers linked data about science research that are being harvested from the Web and are supplemented and edited by community members. We use ontologies to incorporate semantics to detect conflicts and resolve inconsistencies, and to infer new relations or proof statements with a reasoning engine. We consider a semantic web subject to changes in the knowledge base, the underlying ontology or the rule set that governs the reasoning. In this paper we explore the idea of trust where each change to the knowledge base is analyzed as to what subset of the knowledge base can still be trusted. We present algorithms that adapt the reasoner such that, when proving a goal, it does a simple retrieval when it encounters trusted items and backward chaining over untrusted items. We provide an evaluation of our proposed modifications that show that our algorithm is conservative and that it provides significant gains in performance for certain queries.

Studia Logica - An International Journal for Symbolic Logic, 2001

2012

Abstract Trust is a mechanism for managing the uncertainty about autonomous entities and the information they store, and so can play an important role in any decentralized system. As a result, trust has been widely studied in multi-agent systems and related fields such as the semantic web. Here, we introduce a formal system of argumentation that can be used to reason using information about trust.

2010

Abstract. Trust is a mechanism for managing the uncertainty about autonomous entities and the information they store, and so can play an important role in any decentralized system. As a result, trust has been widely studied in multiagent systems and related fields such as the semantic web. Here we introduce a formal system of argumentation that can be used to reason about trust. We explore some of the simple properties of the system and we illustrate its application on a benchmark problem from the trust literature.

2005

One of the most difficult problems in multiagent systems involves representing knowledge and beliefs of agents in dynamic environments. New perceptions modify an agent's current knowledge about the world, and consequently its beliefs. Such revision and updating process should be performed efficiently by the agent, particularly in the context of real time constraints. This paper introduces an argument-based logic programming language called Observation-based Defeasible Logic Programming (ODeLP).

… Distributed Computing III, 2009

Based on the plethora of proposals and standards for logic-and rulebased reasoning for the Semantic Web (SW), a key factor for the success of SW agents is interoperability of reasoning tasks. This paper reports on the first steps towards a framework for interoperable reasoning among agents in the SW that deploys third-party trusted reasoning services. This way, agents can exchange their arguments, without the need to conform to a common rule or logic paradigm -via an external reasoning service, the receiving agent can grasp the semantics of the received rule set. The paper presents how a multi-agent system was extended with a third-party trusted defeasible reasoning service, which offers agents the ability of reasoning with incomplete and inconsistent information. In addition, a brokering trade scenario is presented that illustrates the usability of the approach.

2008

Interpreting Semantic Web Data by different human experts can end up in scenarios, where each expert comes up with different and conflicting ideas what a concept can mean and how they relate to other concepts. Software agents that operate on the Semantic Web have to deal with similar scenarios where the interpretation of Semantic Web data that describes the heterogeneous sources becomes contradicting.

2011

Abstract. Trust is an approach to managing the uncertainty about autonomous entities and the information they store, and so can play an important role in any decentralized system. As a result, trust has been widely studied in multiagent systems and related fields such as the semantic web. Here we introduce a simple approach to reasoning about trust with logic, describe how it can be combined with reasoning about beliefs using logic, and demonstrate its use on an example.

Journal of Logic and Computation, 2012

Trust models as thus far described in the literature can be seen as a monolithic structure: a trust model is provided with a variety of inputs and the model performs calculations, resulting in a trust evaluation as output. The agent has no direct method of adapting its trust model to its needs in a given context. In this article, we propose a first step in allowing an agent to reason about its trust model, by providing a method for incorporating a computational trust model into the cognitive architecture of the agent. By reasoning about the factors that influence the trust calculation the agent can effect changes in the computational process, thus proactively adapting its trust model. We give a declarative formalization of this system using a multi-context system and we show that three contemporary trust models, BRS, ReGReT and ForTrust can be incorporated into a BDI reasoning system using our framework.