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.

The CIFF Proof Procedure for Abductive Logic Programming with Constraints: Deflnition, Implementation and a Web Application

Abstract: Abduction has found broad application as a powerful tool for hypothetical reasoning with incomplete knowledge, which can be handled by labeling some pieces of information as abducibles, i.e. as possible hypotheses that can be assumed to hold, provided that they are consistent with the given knowledge base. Attempts to make the abductive reasoning an effective computational tool gave rise to Abductive Logic Programming (ALP) which combines abduction with standard logic programming. A number of so-called proof procedures for ALP have been proposed in the literature, e.g. the IFF procedure, the Kakas and Mancarella procedure and the SLDNFA procedure, which rely upon extensions of different semantics for logic programming. ALP has also been integrated with Constraint Logic Programming (CLP), in order to combine abductive reasoning with an arithmetic tool for constraint solving. In recent years, many proof procedures for abductive logic programming with constraints have been proposed, including ACLP and the A-System which have been applied to many fields, e.g. multi-agent systems, scheduling, integration of information. This dissertation describes the development of a new abductive proof procedure with constraints, namely the CIFF proof procedure. The description is both at the theoretical level, giving a formal definition and a soundness result with respect to the three-valued completion semantics, and at the implementative level with the implemented CIFF System 4.0 as a Prolog meta-interpreter. The main contributions of the CIFF proof procedure are the advances in the expressiveness of the framework with respect to other frameworks for abductive logic programming with constraints, and the overall computational performances of the implemented system. The second part of the dissertation presents a novel application of the CIFF proof procedure as the computational engine of a tool, the CIFFWEB system, for checking and (possibly) repairing faulty web sites. Indeed, the exponential growth of the WWW raises the question of maintaining and automatically repairing web sites, in particular when the designers of these sites require them to exhibit certain properties at both structural and data level. The capability of maintaining and repairing web sites is also important to ensure the success of the Semantic Web vision. As the Semantic Web relies upon the definition and the maintenance of consistent data schemas (XML/XMLSchema, RDF/RDFSchema, OWL and so on), tools for reasoning over such schemas (and possibly extending the reasoning to multiple web pages) show great promise. The CIFFWEB system is such a tool which allows to verify and to repair XML web sites instances, against sets of requirements which have to be fulfilled, through abductive reasoning. We define an expressive characterization of rules for checking and repairing web sites’ errors and we do a formal mapping of a fragment of a well-known XML query language, namely Xcerpt, to abductive logic programs suitable to fed as input to the CIFF proof procedure. Finally, the CIFF proof procedure detects the errors and possibly suggests modifications to the XML instances to repair them. The soundness of this process is directly inherited from the soundness of CIFF.

Peirce's last philosophic will and testament: Uberty in the logic of instinctive reasoning

Abstract: In essential continuity with his argument for Musement in “A Neglected Argument for the Reality of God” of 1908, Peirce’s last unfinished papers MS 682 and MS 683 of 1913 contain his self-considered “legacy” contribution to the history of logic, as well as reprising his career-long integration of epistemological and ontological dimensions of an idealismrealism, which he expressed as a “universe perfused with signs.” Peirce’s semiotic universe involves the coalescent plasticity of evolutionary nature and mind, the heuristic front edge of which is the quale-consciousness of instinct-rooted abductive inference, for which he introduced the technical term uberty (“gravid with new births”), in distinction from deduction and induction, in reasoning

Rule-based reasoning in connectionist networks

Abstract: This thesis addresses the problem of efficiently representing large knowledge bases and performing a class of inferences extremely fast. The speed of reasoning depends on a number of factors including the expressiveness of the system, the nature of the computational architecture and the representation methodology. A number of knowledge representation and reasoning schemes have given very high emphasis to just one of such issues while neglecting others. This dissertation work is based on the belief that it is beneficial to take an approach where all such issues are simultaneously addressed. With respect to the issue of computational architecture, it is argued that a connectionist architecture has some significant advantages. Having made that choice, we explore how to represent and reason with rules involving multi-place predicates and variables in a connectionist architecture. The main hurdle that needs to be crossed in order to be able to achieve this is the dynamic binding problem. In essence, the problem is that of representing the dynamic grouping of nodes located in different parts of the network. We use what we refer to as the synchronous activation approach to solve the binding problem. Simply stated, the idea is just that the dynamic grouping of a set of nodes is represented by the fact that all those nodes fire synchronously. This happens to be a solution that is technically attractive as well as biologically plausible. Incorporating the synchronous activation approach to solve the binding problem, rule-based forward and backward reasoning systems have been designed to perform deductive inferences. These systems represent knowledge very efficiently: the number of nodes and links required is only linear in the size of the knowledge base. They also perform inferences extremely fast: an inference takes time that is just linear in the length of the shortest proof. We also examine various ways of extending the expressiveness and reasoning abilities of these systems. An alternative representation scheme more amenable to learning is also presented along with a proposal for doing abductive reasoning in connectionist networks.

Biomorphism and Models in Design

Abstract: Biomorphism is a form of biomimicry that involves the use of biological forms as models for the design of artifacts such as airplanes, computers, and islands. This article characterizes biomorphism as a form of abductive reasoning. It also provides an overview of biomorphic design in terms of the parameters of similarity and utility. The cognitive significance of biomorphism is reviewed with respect to research in pareidolia and consumer choice. The normative status of biomorphism is considered in light of its tendency to conflate natural and artificial categories.