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Automated Deduction

The Experts below are selected from a list of 3567 Experts worldwide ranked by ideXlab platform

Xingxing He – 1st expert on this subject based on the ideXlab platform

  • contradiction separation based dynamic multi clause synergized Automated Deduction
    Information Sciences, 2018
    Co-Authors: Yang Xu, Shuwei Chen, Xiaomei Zhong, Xingxing He

    Abstract:

    Abstract Resolution as a famous rule of inference has played a key role in Automated reasoning for over five decades. A number of variants and refinements of resolution have been also studied, essentially, they are all based on binary resolution, that is, the cutting rule of the complementary pair while every Deduction involves only two clauses. In the present work, we consider an extension of binary resolution rule, which is proposed as a novel contradiction separation based inference rule for Automated Deduction, targeted for dynamic and multiple (two or more) clauses handling in a synergized way, while binary resolution is its special case. This contradiction separation based dynamic multi-clause synergized Automated Deduction theory is then proved to be sound and complete. The development of this new extension is motivated not only by our view to show that such a new rule of inference can be generic, but also by our wish that this inference rule could provide a basis for more efficient Automated Deduction algorithms and systems.

  • ISKE – Some synergized clause selection strategies for contradiction separation based Automated Deduction
    2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2017
    Co-Authors: Shuwei Chen, Yang Xu, Yan Jiang, Xingxing He

    Abstract:

    The synergized dynamic contradiction separation based Automated Deduction theory has provided a novel logic based Automated Deduction reasoning framework, which ex­tends the static binary resolution inference rule to a dynamic multiple contradiction separation based Automated Deduction mechanism. This novel contradiction separation based auto­mated Deduction mechanism is characterized as a dynamic, multi-clauses involving, synergized, goal-oriented and robust Automated reasoning framework. In order to further improve the efficiency and feasibility of this novel Automated Deduction mechanism, this paper proposes some strategies for clause or literal selection during the Automated Deduction process, which consider mainly the synergized effect of multi-clauses during the Deduction process. Some examples are put forward to illustrate the feasibility of these proposed strategies.

  • Some synergized clause selection strategies for contradiction separation based Automated Deduction
    2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2017
    Co-Authors: Shuwei Chen, Yang Xu, Yan Jiang, Xingxing He

    Abstract:

    The synergized dynamic contradiction separation based Automated Deduction theory has provided a novel logic based Automated Deduction reasoning framework, which extends the static binary resolution inference rule to a dynamic multiple contradiction separation based Automated Deduction mechanism. This novel contradiction separation based Automated Deduction mechanism is characterized as a dynamic, multi-clauses involving, synergized, goal-oriented and robust Automated reasoning framework. In order to further improve the efficiency and feasibility of this novel Automated Deduction mechanism, this paper proposes some strategies for clause or literal selection during the Automated Deduction process, which consider mainly the synergized effect of multi-clauses during the Deduction process. Some examples are put forward to illustrate the feasibility of these proposed strategies.

Stephen Pulman – 2nd expert on this subject based on the ideXlab platform

  • CADE – Tutorial: Automated Deduction and Natural Language Understanding
    Automated Deduction – CADE-17, 2000
    Co-Authors: Stephen Pulman

    Abstract:

    The purpose of this tutorial is to introduce the Automated Deduction community to a growing area in which their expertise can be applied to a novel set of problems. No knowledge of natural language processing will be assumed. (If you have time for some background reading, James Allen’s ‘Natural Language Understanding’, 2nd edition, Addison Wesley, 1995 can be recommended).

  • tutorial Automated Deduction and natural language understanding
    Conference on Automated Deduction, 2000
    Co-Authors: Stephen Pulman

    Abstract:

    The purpose of this tutorial is to introduce the Automated Deduction community to a growing area in which their expertise can be applied to a novel set of problems. No knowledge of natural language processing will be assumed. (If you have time for some background reading, James Allen’s ‘Natural Language Understanding’, 2nd edition, Addison Wesley, 1995 can be recommended).

  • tutorial Automated Deduction and natural language understanding
    Lecture Notes in Computer Science, 2000
    Co-Authors: Stephen Pulman

    Abstract:

    The purpose of this paper is to introduce the Automated Deduction community to a growing area in which their expertise can be applied to a novel set of problems. I will describe and illustrate some of the areas in which Natural Language Understanding interacts with theorem proving.

Shuwei Chen – 3rd expert on this subject based on the ideXlab platform

  • contradiction separation based dynamic multi clause synergized Automated Deduction
    Information Sciences, 2018
    Co-Authors: Yang Xu, Shuwei Chen, Xiaomei Zhong, Xingxing He

    Abstract:

    Abstract Resolution as a famous rule of inference has played a key role in Automated reasoning for over five decades. A number of variants and refinements of resolution have been also studied, essentially, they are all based on binary resolution, that is, the cutting rule of the complementary pair while every Deduction involves only two clauses. In the present work, we consider an extension of binary resolution rule, which is proposed as a novel contradiction separation based inference rule for Automated Deduction, targeted for dynamic and multiple (two or more) clauses handling in a synergized way, while binary resolution is its special case. This contradiction separation based dynamic multi-clause synergized Automated Deduction theory is then proved to be sound and complete. The development of this new extension is motivated not only by our view to show that such a new rule of inference can be generic, but also by our wish that this inference rule could provide a basis for more efficient Automated Deduction algorithms and systems.

  • ISKE – Some synergized clause selection strategies for contradiction separation based Automated Deduction
    2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2017
    Co-Authors: Shuwei Chen, Yang Xu, Yan Jiang, Xingxing He

    Abstract:

    The synergized dynamic contradiction separation based Automated Deduction theory has provided a novel logic based Automated Deduction reasoning framework, which ex­tends the static binary resolution inference rule to a dynamic multiple contradiction separation based Automated Deduction mechanism. This novel contradiction separation based auto­mated Deduction mechanism is characterized as a dynamic, multi-clauses involving, synergized, goal-oriented and robust Automated reasoning framework. In order to further improve the efficiency and feasibility of this novel Automated Deduction mechanism, this paper proposes some strategies for clause or literal selection during the Automated Deduction process, which consider mainly the synergized effect of multi-clauses during the Deduction process. Some examples are put forward to illustrate the feasibility of these proposed strategies.

  • Some synergized clause selection strategies for contradiction separation based Automated Deduction
    2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2017
    Co-Authors: Shuwei Chen, Yang Xu, Yan Jiang, Xingxing He

    Abstract:

    The synergized dynamic contradiction separation based Automated Deduction theory has provided a novel logic based Automated Deduction reasoning framework, which extends the static binary resolution inference rule to a dynamic multiple contradiction separation based Automated Deduction mechanism. This novel contradiction separation based Automated Deduction mechanism is characterized as a dynamic, multi-clauses involving, synergized, goal-oriented and robust Automated reasoning framework. In order to further improve the efficiency and feasibility of this novel Automated Deduction mechanism, this paper proposes some strategies for clause or literal selection during the Automated Deduction process, which consider mainly the synergized effect of multi-clauses during the Deduction process. Some examples are put forward to illustrate the feasibility of these proposed strategies.