Abductive reasoning

About: Abductive reasoning is a research topic. Over the lifetime, 1917 publications have been published within this topic receiving 44645 citations. The topic is also known as: abduction & abductive inference.

Using Extended Logic Programs to Formalize Commonsense Reasoning

Abstract: In this dissertation, we investigate how commonsense reasoning can be formalized by using extended logic programs. In this investigation, we first use extended logic programs to formalize inheritance hierarchies with exceptions by adopting McCarthy's simple abnormality formalism to express uncertain knowledge. In our representation, not only credulous reasoning can be performed but also the ambiguity-blocking inheritance and the ambiguity-propagating inheritance in skeptical reasoning are simulated. In response to the anomalous extension problem, we explore and discover that the intuition underlying commonsense reasoning is a kind of forward reasoning. The unidirectional nature of this reasoning is applied by many reformulations of the Yale shooting problem to exclude the undesired conclusion. We then identify defeasible conclusions in our representation based on the syntax of extended logic programs. A similar idea is also applied to other formalizations of commonsense reasoning to achieve such a purpose.

Uncertainty Reasoning Based on Lattice-Valued Propositional Logic L6

Abstract: Uncertainty reasoning is one of important directions in the research field of artificial intelligence. Uncertainty reasoning theory and methods based on lattice-valued logic is sound in its strict logical foundation. In this paper, some methods for selecting appropriate parameters in the uncertainty reasoning process based on lattice-valued propositional logic Lscr6 are proposed

Abductive reasoning for image interpretation based on spatial concrete domains and description logics

Abstract: Image interpretation aims not only at detecting and recognizing objects in a scene but also at deriving a semantic description considering contextual information in the whole scene. Image interpretation can be formalized as an abductive reasoning problem, i.e. an inference to the best explanation using a background knowledge. In this work, we present a framework using a tableau method for generating and selecting potential explanations of the given image when the background knowledge is encoded in description logics, and includes concepts describing objects and their spatial relations. The best explanation is selected according to a minimality criterion based on the satisfaction degree of spatial relations between the objects, computed in concrete domains.

A Logic Programming Framework for the Abductive Inference of Intentions in Cooperative Dialogues

Abstract: In this paper we propose a general logic programming framework allowing the recognition of plans and intentions behind speech acts through abductive reasoning. These inferences enables each agent to have an active participation in dialogues, namely in cooperative informationseeking dialogues. In our framework the possible actions, events, states and world knowledge are represented by extended logic programs (LP with explicit negation) and the abductive inference process is modeled by a framework wich is based on the Well Founded Semantics augmented with explicit negation (WFSX) and contradiction removal semantics (CRSX) ([PAA92]). It will be shown how this framework supports abductive reasoning with Event Calculus ([Esh88]) and some classical examples in the domain of information-seeking dialogues will be shown ([Lit85, Pol86]). Finally, some open problems will be pointed out.

Model Development and Initial Validation

Abstract: Models and frameworks have been described as platforms for resolving contemporary real-world challenges. This is due to their ability to provide a symbolic depiction of real-world scenarios. As such, various studies have relied on models and frameworks in proffering solutions to different problems. A prevalence of models and frameworks developed and validated through overt reliance on quantitative data have been observed in the literature. This is particularly the case with model development in the Architectural, Engineering and Construction (AEC) disciplines. In chapter, the process of model development and validation based on qualitative data is explicated. A three-tier approach to model validation which had been hitherto deployed in the validation and verification of Human, Social, Cultural and Behavioural (HSCB) models was utilized. Also, the systematic combining approach was used in establishing the model-theory fit as suggested in similar studies which had adopted abductive reasoning logic. In summary, this chapter provides a step by step account of the approaches which can be deployed in model validation and verification using qualitative data set in AEC research using a viable infrastructure delivery systems model (VIDM) exemplar.