An ontology of physical causation as a basis for assessing causation in fact and attributing legal responsibility

Lehmann, Jos; Gangemi, Aldo

doi:10.1007/s10506-007-9035-3

Cited by 15 publications

(12 citation statements)

References 7 publications

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“…As described in Lehmann (2003), (legal) causality, responsibility, liability and guilt are closely intertwined concepts in legal reasoning aimed at compensating for wrong doing. The work described here is based on Lehmann (2003), but deviates from his more recent work of Lehmann et al (2004) and Lehmann and Gangemi (2006) in that it has a stronger AI flavour.…”

Section: Liabilitymentioning

confidence: 62%

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Commonsense Causal Explanation in a Legal Domain

Hoekstra

Breuker

2007

Artif Intell Law

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Abstract. In this paper, we present an approach to commonsense causal explanation of stories that can be used for automatically determining the liable party in legal case descriptions. The approach is based on LRICore, a core ontology for law that takes a commonsense perspective. Aside from our thesis that in the legal domain many terms still have a strong commonsense flavour, the descriptions of events in legal cases, as e.g. presented at judicial trials, are cast in commonsense terms as well. We present design principles for representing commonsense causation, and describe a process-based approach to automatic identification of causal relations in stories, which are described in terms of the core ontology. The resulting causal explanation forms a necessary condition for determining the liability and responsibility of agents that play a role in the case. We describe the basic architecture and working of DIRECT, the demonstrator we are constructing to test the validity of our process oriented view on commonsense causation. This view holds that causal relations are in fact abstractions constructed on the basis of our commonsense understanding of physical and mental processes.

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Section: Liabilitymentioning

confidence: 62%

“…The ontological approach to causation in fact described in Lehmann et al (2004) and Lehmann and Gangemi (2006), defines causal dependencies within the framework of the DOLCE ontology, see e.g. Gangemi et al (2002).Causal relations relate very simple (types of) events that change a single aspect of a single object.…”

Section: Ontologymentioning

confidence: 99%

Commonsense Causal Explanation in a Legal Domain

Hoekstra

Breuker

2007

Artif Intell Law

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“…We refer interested readers to Boley et al (2007) for more information. Rules, as a logic paradigm, are quite important, as they provide the capability of explaining why a particular decision is reached (Besnard et al, 2008;Diouf et al, 2007;Lehmann and Gangemi, 2007). This becomes possible by tracing back the inference chain of the executed rules and revealing the conditions and any intermediate data inferred during the reasoning process.…”

Section: • Normative Rulesmentioning

confidence: 99%

“…a to explain the reasoning logic of the system decisions through giving the relevant feedback and the guidance (Besnard et al, 2008;Lehmann and Gangemi, 2007) b to enable users to mediate system decisions through the given feedback c to aid interaction between the users and the environment, since they concisely describe the properties of the environment and the various concepts used in the environment (Ranganathan et al, 2003) • alleviation of imperfectness through consistency checking of the context…”

Section: A Merged Approachmentioning

confidence: 99%

Formal modelling, knowledge representation and reasoning for design and development of user-centric pervasive software: a meta-review

Soylu

Causmaecker

Preuveneers

et al. 2011

IJMSO

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Abstract:Increasing demand for large scale and highly complex systems and applications, particularly with the emergence of pervasive computing and the impact of adaptive systems, introduces significant challenges for software development, as well as for user-machine interaction. Therefore, a perspective shift on software development and user-machine interaction is required. An amalgamation of model driven development and ontologies has been envisaged as a promising direction in recent literature. In this paper, we investigate this merged approach and conclude that a merger of both approaches, from formal modelling and knowledge representation perspective, on the one hand enables use of ontologies at run-time together with rules, prominently in terms of run-time reasoning, dynamic adaptations, software intelligibility, self-expressiveness, user involvement, and user situation awareness; and on the other hand at development time, prominently in terms of automated and incremental code generation, requirement adaptability, preservation of application knowledge, and validation and verification of structural and behavioural properties of the software. The core contribution of this paper lies in providing an elaborate and exploratory discussion of the problem and solution spaces along with a multidisciplinary meta-review and identification of complementary efforts in literature required to realise a merged approach.

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“…complete or partial adoption, external control and distribution of accountability, emergence, negotiation, trustfulness); -the causal relations that characterize them, e.g. according to the set-up of the DnS-based treament of causal relations presented in Lehmann and Gangemi [31].…”

Section: In Sect 33)mentioning

confidence: 99%

Norms and plans as unification criteria for social collectives

Gangemi

2008

Auton Agent Multi-Agent Syst

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Based on the paradigm of Constructive Descriptions and Situations, we introduce NIC, an ontology of social collectives that includes social agents, plans, norms, and the conceptual relations between them. Norms are distinguished from plans, and their relations are formalized. A typology of social collectives is also proposed, including collection of agents, knowledge community, intentional collective, and normative intentional collective. NIC, represented as a first-order theory as well as a description logic for applications requiring automated reasoning, provides the expressivity to talk about the contexts (social, informational, circumstantial, and conceptual), in which collectives make and produce sense within the interplay of plans and norms.

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An ontology of physical causation as a basis for assessing causation in fact and attributing legal responsibility

Cited by 15 publications

References 7 publications

Commonsense Causal Explanation in a Legal Domain

Commonsense Causal Explanation in a Legal Domain

Formal modelling, knowledge representation and reasoning for design and development of user-centric pervasive software: a meta-review

Norms and plans as unification criteria for social collectives

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