Constructing Induction Rules for Deductive Synthesis Proofs
01 Mar 2006-Electronic Notes in Theoretical Computer Science (Elsevier Science Publishers B. V.)-Vol. 153, Iss: 1, pp 3-21
TL;DR: It is shown that a combination of rippling and the use of meta-variables as a least-commitment device can provide novelty in induction rule construction techniques that can introduce novel recursive structures.
About: This article is published in Electronic Notes in Theoretical Computer Science.The article was published on 2006-03-01 and is currently open access. It has received 2969 citations till now. The article focuses on the topics: Recursion & Mathematical proof.
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References
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01 Jan 1999
TL;DR: The topics in LNAI include automated reasoning, automated programming, algorithms, knowledge representation, agent-based systems, intelligent systems, expert systems, machine learning, natural-language processing, machine vision, robotics, search systems, knowledge discovery, data mining, and related programming languages.
Abstract: LNAI was established in the mid-1980s as a topical subseries of LNCS focusing on artificial intelligence. This subseries is devoted to the publication of state-of-the-art research results in artificial intelligence, at a high level and in both printed and electronic versions making use of the well-established LNCS publication machinery. As with the LNCS mother series, proceedings and postproceedings are at the core of LNAI; however, all other sublines are available for LNAI as well. The topics in LNAI include automated reasoning, automated programming, algorithms, knowledge representation, agent-based systems, intelligent systems, expert systems, machine learning, natural-language processing, machine vision, robotics, search systems, knowledge discovery, data mining, and related programming languages.
3,464 citations
•
01 Jan 1979
TL;DR: This paper presents a meta-modelling simulation of the response of the immune system to changes in the environment through the course of natural selection.
Abstract: • Constraint domains in which the possible values that a variable can take are restricted to a finite set. • Examples: Boolean constraints, or integer constraints in which each variable is constrained to lie in within a finite range of integers. • Widely used in constraint programming. • Many real problems can be easily represented using constraint domains, e.g.: scheduling, routing and timetabling. • They involve choosing amongst a finite number of possibilities. • Commercial importance to many businesses: e.g. deciding how air crews should be allocated to aircraft flights. • Developed methods by different research communities: Arc and node consistency techniques (artificial intelligence). Bounds propagation techniques (constraint programming). Integer programming (operations research).
1,123 citations
••
TL;DR: This paper surveys the development of the operational semantics as well as the improvement of the implementation of functional logic languages.
Abstract: Functional and logic programming are the most important declarative programming paradigms, and interest in combining them has grown over the last decade. Early research concentrated on the definition and improvement of execution principles for such integrated languages, while more recently efficient implementations of these execution principles have been developed so that these languages became relevant for practical applications. In this paper, we survey the development of the operational semantics as well as the improvement of the implementation of functional logic languages.
489 citations
••
28 Jul 2003TL;DR: The IsaPlanner as mentioned in this paper is a generic framework for proof planning in the interactive theorem prover Isabelle, which facilitates the encoding of reasoning techniques, which can be used to conjecture and prove theorems automatically.
Abstract: IsaPlanner is a generic framework for proof planning in the interactive theorem prover Isabelle. It facilitates the encoding of reasoning techniques, which can be used to conjecture and prove theorems automatically. This paper introduces our approach to proof planning, gives and overview of IsaPlanner, and presents one simple yet effective reasoning technique.
225 citations
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TL;DR: It is shown how the failure if rippling can be used in bridging gaps in the search for inductive proofs, and a novel theorem-proving architecture for supporting the automatic discovery of eureka steps is presented.
Abstract: Proof by mathematical induction gives rise to various kinds of eureka steps, e.g., missing lemmata and generalization. Most inductive theorem provers rely upon user intervention in supplying the required eureka steps. In contrast, we present a novel theorem-proving architecture for supporting the automatic discovery of eureka steps. We build upon rippling, a search control heuristic designed for inductive reasoning. We show how the failure if rippling can be used in bridging gaps in the search for inductive proofs.
184 citations