Mapping deontic operators to abductive expectations

Alberti, Marco; Gavanelli, Marco; Lamma, Evelina; Mello, Paola; Torroni, Paolo; Sartor, Giovanni

doi:10.1007/s10588-006-9544-8

Cited by 31 publications

(38 citation statements)

References 31 publications

(30 reference statements)

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“…Poole [51] showed, more generally, that, by making implicit assumptions, like normal-bird(X), explicit, default rules in default logic [57] can be translated into "hard" or "strict" rules in an abductive framework. 1 Bondarenko et al [9] showed that abduction with an argumentation interpretation can be used to generalize many other existing formalisms for default reasoning. Poole [52] showed that, by associating probabilities with assumptions, abductive logic programs can also represent Bayesian networks.…”

Section: Abductive Logic Programmingmentioning

confidence: 99%

“…The approach that is most closely related to the one in this paper is that of Alberti et al [1], which maps deontic operators into abducible deontic predicates in ALP, using a proof procedure SCIFF, based on the IFF proof procedure of [21]. Here is a simplified variant of an example from [1], representing an obligation and a prohibition as integrity constraints: The first constraint means that, if agent A sends to agent B a query for Info at time T1 for response with maximum delay D, then B is expected to reply with either an inform or a refuse message by D time units later.…”

Section: Abductive Expectations In Sciffmentioning

confidence: 99%

“…At various places in this paper, we compare the ALP approach with that of standard deontic logic and some of its variants, production systems, Horty's default deontic logic, constrained optimisation, SBVR (Semantics of Business Vocabulary and Rules [61] and SCIFF [1]. The comparison with constrained optimisation shows that the separation in ALP between goals and preferences is a standard approach in practical problem solving systems.…”

Section: Introductionmentioning

confidence: 99%

“…However, the approach most closely related to the one of this paper is that of SCIFF [1], which uses ALP to specify and verify interaction in multi-agent systems. Alberti et al [1] compare SCIFF with modal deontic logics, but do not discuss the treatment of conflicting obligations or contrary-to-duty obligations.…”

Section: Introductionmentioning

confidence: 99%

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Obligation as Optimal Goal Satisfaction

Kowalski

Satoh

2017

J Philos Logic

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Formalising deontic concepts, such as obligation, prohibition and permission, is normally carried out in a modal logic with a possible world semantics, in which some worlds are better than others. The main focus in these logics is on inferring logical consequences, for example inferring that the obligation O q is a logical consequence of the obligations O p and O (p → q). In this paper we propose a nonmodal approach in which obligations are preferred ways of satisfying goals expressed in first-order logic. To say that p is obligatory, but may be violated, resulting in a less than ideal situation s, means that the task is to satisfy the goal p ∨ s, and that models in which p is true are preferred to models in which s is true. Whereas, in modal logic, the preference relation between possible worlds is part of the semantics of the logic, in this non-modal approach, the preference relation between first-order models is external to the logic. Although our main focus is on satisfying goals, we also formulate a notion of logical consequence, which is comparable to the notion of logical consequence in modal deontic logic. In this formalisation, an obligation O p is a logical consequence of goals G, when p is true in all best models of G. We show how this non-modal approach to the treatment of deontic concepts deals with problems of contrary-to-duty obligations and normative conflicts, and argue that the approach is useful for many other applications, including abductive explanations, defeasible reasoning, combinatorial optimisation, and reactive systems of the production system variety.

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Section: Abductive Logic Programmingmentioning

confidence: 99%

Section: Abductive Expectations In Sciffmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Obligation as Optimal Goal Satisfaction

Kowalski

Satoh

2017

J Philos Logic

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“…The SCIFF framework [23] is related to our work in that it also uses constraint resolution to reduce the scope of expectations to avoid conflict -expectation is a concept closely related to norms [24]. For instance, in that work, E(p, X ), 0 ≤ X ≤ 10 means that p is expected to hold true between 0 and 10, and EN(p, Y ), Y > 5 means that p is expected not to hold true when Y is greater than 5; positive expectations are related to obligations (and are implicitly existentially quantified) and negative expectations are related to prohibitions (and are implicitly universally quantified).…”

Section: Related Workmentioning

confidence: 99%

Conflict Resolution in Norm-Regulated Environments Via Unification and Constraints

Kollingbaum

Vasconcelos

García-Camino

et al. 2008

Declarative Agent Languages and Technologies V

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Abstract. We present a novel mechanism for the detection and resolution of conflicts within norm-regulated virtual environments, populated by agents whose behaviours are regulated by explicit obligations, permissions and prohibitions. A conflict between norms arises when an action is simultaneously prohibited and obliged or prohibited and permitted. In this paper, we use first-order unification and constraint satisfaction to detect and resolve such conflicts, introducing a concept of norm curtailment. A flexible and robust algorithm for norm adoption is presented and aspects of indirect conflicts and conflicts across delegation of actions between agents is discussed.

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