Deon  + : Abduction and Constraints for Normative Reasoning

Alberti, Marco; Gavanelli, Marco; Lamma, Evelina

doi:10.1007/978-3-642-29414-3_17

Cited by 4 publications

(2 citation statements)

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“…SCIFF has been continuously developed and improved in the past few years, and now it is the computational basis for many applications, such as contracting in the semantic web [3] and normative systems [11]; it is considerably faster, more robust, and provides more features, including integration with constrained optimization [24].…”

Section: Introductionmentioning

confidence: 99%

The CHR-based Implementation of the SCIFF Abductive System

Alberti

Gavanelli

Lamma

2013

Fundamenta Informaticae

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Abduction is a form of inference that supports hypothetical reasoning and has been applied to a number of domains, such as diagnosis, planning, protocol verification. Abductive Logic Programming (ALP) is the integration of abduction in logic programming. Usually, the operational semantics of an ALP language is defined as a proof procedure.The first implementations of ALP proof-procedures were based on the meta-interpretation technique, which is flexible but limits the use of the built-in predicates of logic programming systems. Another, more recent, approach exploits theoretical results on the similarity between abducibles and constraints. With this approach, which bears the advantage of an easy integration with built-in predicates and constraints, Constraint Handling Rules has been the language of choice for the implementation of abductive proof procedures. The first CHR-based implementation mapped integrity constraints directly to CHR rules, which is an efficient solution, but prevents defined predicates from being in the body of integrity constraints and does not allow a sound treatment of negation by default.In this paper, we describe the CHR-based implementation of the SCIFF abductive proof-procedure, which follows a different approach. The SCIFF implementation maps integrity constraints to CHR constraints, and the transitions of the proof-procedure to CHR rules, making it possible to treat default negation, while retaining the other advantages of CHR-based implementations of ALP proofprocedures.

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Section: Introductionmentioning

confidence: 99%

The CHR-based Implementation of the SCIFF Abductive System

Alberti

Gavanelli

Lamma

2013

Fundamenta Informaticae

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“…The modelling of institutional frameworks has been subject to research for several decades (a comprehensive discussion appears in Jones and Sergot (1993) and more recently in Grossi (2007)). Looking at the literature on the computational implementation of policies and institutional frameworks, one finds that they are often encoded as formulas in some logic language, where some components of the formula represent notions of obligation, permission and prohibition, which are linked by rules (Alberti et al, 2012). The advantages of this form of implementation are three-fold:…”

Section: Introductionmentioning

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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Abductive Logic Programming for Normative Reasoning and Ontologies

Gavanelli

Lamma

Riguzzi

et al. 2017

New Frontiers in Artificial Intelligence

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Abductive Logic Programming (ALP) has been exploited to\ud formalize societies of agents, commitments and norms, taking advantage from ALP operational support as a (static or dynamic) verification\ud tool. In [7], the most common deontic operators (obligation, prohibition, permission) are mapped into the abductive expectations of an ALP\ud framework for agent societies. Building upon such correspondence, in [5],\ud authors introduced Deon+ , a language where obligation and prohibition\ud deontic operators are enriched with quantification over time, by means\ud of ALP and Constraint Logic Programming (CLP).\ud In recent work [30, 31], we have shown that the same ALP framework\ud can be suitable to represent Datalog± ontologies. Ontologies are a fundamental component of both the Semantic Web and knowledge-based\ud systems, even in the legal setting, since they provide a formal and machine manipulable model of a domain.\ud In this work, we show that ALP is a suitable framework for representing\ud both norms and ontologies. Normative reasoning and ontological query\ud answering are obtained by applying the same abductive proof procedure,\ud smoothly achieving their integration. In particular, we consider the ALP\ud framework named SCIFF and derived from the IFF abductive framework, able to deal with existentially (and universally) quantified variables\ud in rule heads and CLP constraints.\ud The main advantage is that this integration is achieved within a single\ud language, grounded on abduction in computational logic

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Deon + : Abduction and Constraints for Normative Reasoning

Cited by 4 publications

References 36 publications

The CHR-based Implementation of the SCIFF Abductive System

The CHR-based Implementation of the SCIFF Abductive System

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

Abductive Logic Programming for Normative Reasoning and Ontologies

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