Ambient intelligence (AmI) proposes pervasive information systems composed of autonomous agents embedded within the environment who, in orchestration, complement human activity in an intelligent manner. As such, it is an interesting and challenging application area for many computer science fields and approaches. A critical issue in such application scenarios is that the agents must be able to acquire, exchange, and evaluate knowledge about the environment, its users, and their activities. Knowledge populated between the agents in such systems may be contextually dependent, ambiguous, and incomplete. Conflicts may thus naturally arise, that need to be dealt with by the agents in an autonomous way. In this survey, we relate AmI to the area of knowledge representation and reasoning (KR), where conflict resolution has been studied for a long time. We take a look at a number of KR approaches that may be applied: context modelling, multi-context systems, belief revision, ontology evolution and debugging, argumentation, preferences, and paraconsistent reasoning. Our main goal is to describe the state of the art in these fields, and to draw attention of researchers to important theoretical issues and practical challenges that still need to be resolved, in order to reuse the results from KR in AmI systems or similar complex and demanding applications.

While several interesting argumentation-based semantics for defeasible logic programs have been proposed, to our best knowledge, none of these approaches is able to fully handle the closure under strict rules in a sufficient manner: they are either not closed, or they use workarounds such as transposition of rules which violates desired directionality of logic programming rules. We propose a novel argumentation-based semantics, in which the status of arguments is determined by attacks between newly introduced conflict resolutions instead of attacks between arguments. We show that the semantics is closed w.r.t. strict rules and respects directionality of rules, as well as other desired properties previously published in the literature.

Abstract. We show how defeasible reasoning can be embedded into ABF. Differently from other proposals, we do not encode the conflict resolution mechanism for defeasible rules into the ABF's deductive systems. Instead, we formalize the notions of conflict and conflict resolution and make them part of the extended ABF framework (XABF). This improves the control over the conflict resolution process, and allows to devise and compare different domain-dependent conflict resolution strategies. We also show, that no matter which conflict resolution strategy is used, our framework is able to guarantee certain desired properties.

Argumentation is one of the most popular approaches of defining a non-monotonic formalism and several argumentation based semantics were proposed for defeasible logic programs. Recently, a new approach based on notions of conflict resolutions was proposed, however with declarative semantics only. This paper gives a more procedural counterpart by developing skeptical and credulous argument games for complete semantics and soundness and completeness theorems for both games are provided. After that, distribution of defeasible logic program into several contexts is investigated and both argument games are adapted for multicontext system.