Normative Systems Represented as Hybrid Knowledge Bases

Alberti, Marco; Gomes, Ana Sofía; Gonçalves, Ricardo; Leite, João; Slota, Martin

doi:10.1007/978-3-642-22359-4_23

Cited by 20 publications

(17 citation statements)

References 17 publications

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“…The functions dmax and davg defined above are both distance functions, i.e., satisfy the axioms (1)(2)(3)(4).…”

Section: Propositionmentioning

confidence: 99%

“…Intuitively, instead of designing a unifying language (see e.g., [13,22], and [19] with its reasoner NoHR [18]) to which other languages could be translated, in an MCS the different formalisms and knowledge bases are considered as modules, and means are provided to model the flow of information between them (cf. [1,17,20] and references therein for further motivation on hybrid languages and their connection to MCSs).…”

Section: Introductionmentioning

confidence: 99%

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Minimal Change in Evolving Multi-Context Systems

Gonçalves

Knorr

Leite

2015

Progress in Artificial Intelligence

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Managed Multi-Context Systems (mMCSs) provide a general framework for integrating knowledge represented in heterogeneous KR formalisms. However, mMCSs are essentially static as they were not designed to run in a dynamic scenario. Some recent approaches, among them evolving Multi-Context Systems (eMCSs), extend mMCSs by allowing not only the ability to integrate knowledge represented in heterogeneous KR formalisms, but at the same time to both react to, and reason in the presence of commonly temporary dynamic observations, and evolve by incorporating new knowledge. The notion of minimal change is a central notion in dynamic scenarios, specially in those that admit several possible alternative evolutions. Since eMCSs combine heterogeneous KR formalisms, each of which may require different notions of minimal change, the study of minimal change in eMCSs is an interesting and highly nontrivial problem. In this paper, we study the notion of minimal change in eMCSs, and discuss some alternative minimal change criteria.

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“…The functions dmax and davg defined above are both distance functions, i.e., satisfy the axioms (1)(2)(3)(4).…”

Section: Propositionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Minimal Change in Evolving Multi-Context Systems

Gonçalves

Knorr

Leite

2015

Progress in Artificial Intelligence

Self Cite

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“…2, an agent first detects a norm (1). and launches the Norm's Benefit Evaluator (2). The Evaluator evaluates the parameters' values, Norm's Adoption Ratio, Norm's Yield, Norm's Trust, and Norm's Morality (3).…”

Section: The Proposed Concept Of Norm's Benefit Awareness Componentsmentioning

confidence: 99%

“…Norms and normative systems have received greater attention due to their ability to coordinate agents' interactions [1,2]. In general, norms are integrated with multi-agent systems to guide agents to behave in a socially harmonious way.…”

Section: Introductionmentioning

confidence: 99%

A proposed norms' benefits awareness framework for norms adoption

Itaiwi

Ahmad

Tang

et al. 2014

Proceedings of the 6th International Conference on Information Technology and Multimedia

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Several works have been conducted on norms detection and identification, but almost none has been found to explore the concept of norm's benefit awareness that triggers agents' belief to adopt new norms. The literature discuss norms' adoption by agents which are not aware of the benefits of the adopted norms, but use some mining algorithms to identify the norms from a set of observed events. In this paper, we propose a novel solution to this problem that calculates the benefit of a norm to its utility and subsequently decides to adopt or reject the norm.

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“…Starting with the formal work on the representation of institutional frameworks, it has to be noted that its representation has been a subject of research for several decades. Ever since the British Nationality Act was formalized using Logic Programming by Sergot et al (1986), it has been recognised that non-monotonic formalisms are important to deal with many aspects of rule-based systems in general and institutional frameworks, as well policies and their analysis in particular (Alberti et al, 2011). Policies and norms, specifically, have received much attention using different formalisms, among which defeasible logic (Governatori, 2005;Governatori and Rotolo, 2004) is considered particularly appropriate, along with various executable representations, such as RuleML in (Governatori, 2005).…”

Section: Related Workmentioning

confidence: 99%

I-ABM: combining institutional frameworks and agent-based modelling for the design of enforcement policies

2013

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Computer science advocates institutional frameworks as an effective tool for modelling policies and reasoning about their interplay. In practice, the rules or policies, of which the institutional framework consists, are often specified using a formal language, which allows for the full verification and validation of the framework (e.g. the consistency of policies) and the interplay between the policies and actors (e.g. violations). However, when modelling largescale realistic systems, with numerous decision-making entities, scalability and complexity issues arise making it possible only to verify certain portions of the problem without reducing the scale. In the social sciences, agent-based modelling is a popular tool for analysing how entities interact within a system and react to the system properties. Agent-based modelling allows the specification of complex decision-making entities and experimentation with large numbers of different parameter sets for these entities in order to explore their effects on overall system performance. In this paper we describe how to achieve the best of both worlds, namely verification of a formal specification combined with the testing of large-scale systems with numerous different actor configurations. Hence, we offer an approach that allows for reasoning about policies, policy making and their consequences on a more comprehensive level than has been possible to date. We present the Institutional Agent-Based Model (I-ABM) methodology to combine institutional frameworks with agent-based simulations). We furthermore present J-InstAL, a prototypical implementation of this methodology using the InstAL institutional framework whose specifications can be translated into a computational model under the answer set semantics, and an agent-based simulation based on the JASON tool. Using a simplified contract enforcement example, we demonstrate the functionalities of this prototype and show how it can help to assess an appropriate fine level in case of contract violations.

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Normative Systems Represented as Hybrid Knowledge Bases

Cited by 20 publications

References 17 publications

Minimal Change in Evolving Multi-Context Systems

Minimal Change in Evolving Multi-Context Systems

A proposed norms' benefits awareness framework for norms adoption

I-ABM: combining institutional frameworks and agent-based modelling for the design of enforcement policies

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