Downloads & Free Reading Options - Results

Journal of Automated Reasoning 1996: Volume 17 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_1996_17_index . Next issue: sim_journal-of-automated-reasoning_1996-08_17_1 .

Journal of Automated Reasoning 2001: Volume 27 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_2001_27_index . Next issue: sim_journal-of-automated-reasoning_2001-07_27_1 .

Journal of Automated Reasoning 2002: Volume 28 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_2002_28_index . Next issue: sim_journal-of-automated-reasoning_2002-01_28_1 .

Journal of Automated Reasoning 2002: Volume 28 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_2002_28_index . Next issue: sim_journal-of-automated-reasoning_2002-01_28_1 .

Our objective in this note is to comment briefly on the newly emerging literature on computer-aided proofs in Social Choice Theory. We shall specifically comment on two papers, one by Tang and Lin (2009) and another by Geist and Endriss (2011). We also provide statements and brief descriptions of the results discussed in this note.

Journal of Automated Reasoning 1987: Volume 3 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_1987_3_index . Next issue: sim_journal-of-automated-reasoning_1987-03_3_1 .

Journal of Automated Reasoning is an active peer-reviewed scholarly journal currently published semi-quarterly by Springer. Launched in 1985 by American mathematician and founding-editor Lawrence “Larry” Wos (1930–2020), it is dedicated to the theory, implementation, and applications of logical reasoning by computer. Each issue features original articles on a number of theoretical and applied topics that involve logical reasoning by computer. Published papers cover a range of automatic and interactive reasoning tools including, but not limited to, SAT and SMT solvers, automatic theorem provers based on superposition or tableaux, proof assistants, and program verifiers. Occasional special-focus issues are dedicated to a particular topic of interest or contain selected extended papers presented at relevant conferences and symposia. The Internet Archive Collection contains microfilm published between 1985 and 2007. Journal of Automated Reasoning is found online at: https://www.springer.com/journal/10817   Wikipedia: https://en.wikipedia.org/wiki/Journal_of_Automated_Reasoning   The ISSN is 0168-7433

Ernest Davis computer

STAR is an interactive, interpreted programming language for the development and operation of Artificial Intelligence application systems. The language is intended for use primarily in the development of software application systems which rely on a combination of symbolic processing, central to the vast majority of AI algorithms, with routines and data structures defined in compiled languages such as C, FORTRAN and PASCAL. References to routines and data structures defined in compiled languages are intermixed with symbolic structures in STAR, resulting in a hybrid operating environment in which symbolic and non-symbolic processing and organization of data may interact to a high degree within the execution of particular application systems. The STAR language was developed in the course of a project involving AI techniques in the interpretation of imaging spectrometer data and is derived in part from a previous language called CLIP. The interpreter for STAR is implemented as a program defined in the language C and has been made available for distribution in source code form through NASA's Computer Software Management and Information Center (COSMIC). Contained within this report are the STAR Tutorial Guide, which introduces the language in a step-by-step manner, and the STAR Reference Manual, which provides a detailed summary of the features of STAR.

STAR is an interactive, interpreted programming language for the development and operation of Artificial Intelligence application systems. The language is intended for use primarily in the development of software application systems which rely on a combination of symbolic processing, central to the vast majority of AI algorithms, with routines and data structures defined in compiled languages such as C, FORTRAN and PASCAL. References to routines and data structures defined in compiled languages are intermixed with symbolic structures in STAR, resulting in a hybrid operating environment in which symbolic and non-symbolic processing and organization of data may interact to a high degree within the execution of particular application systems. The STAR language was developed in the course of a project involving AI techniques in the interpretation of imaging spectrometer data and is derived in part from a previous language called CLIP. The interpreter for STAR is implemented as a program defined in the language C and has been made available for distribution in source code form through NASA's Computer Software Management and Information Center (COSMIC). Contained within this report are the STAR Tutorial Guide, which introduces the language in a step-by-step manner, and the STAR Reference Manual, which provides a detailed summary of the features of STAR.

Journal of Automated Reasoning 1985: Volume 1 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_1985_1_index . Next issue: sim_journal-of-automated-reasoning_1985_1_1 .

Journal of Automated Reasoning 1985: Volume 1 , Issue Index. Digitized from IA1513825-03 . Next issue: sim_journal-of-automated-reasoning_1985_1_contents .

Journal of Automated Reasoning 1995: Volume 15 , Issue Index. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_1995-06_14_3 . Next issue: sim_journal-of-automated-reasoning_1995_15_contents .

Journal of Automated Reasoning 1999: Volume 23 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_1999_23_index . Next issue: sim_journal-of-automated-reasoning_1999-07_23_1 .

Journal of Automated Reasoning 2001: Volume 26 , Issue Index. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_2000-11_25_4 . Next issue: sim_journal-of-automated-reasoning_2001_26_contents .

Journal of Automated Reasoning 2001: Volume 26 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_2001_26_index . Next issue: sim_journal-of-automated-reasoning_2001-01_26_1 .

Journal of Automated Reasoning 2005: Volume 35 , Issue Index. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_2005_34_4 . Next issue: sim_journal-of-automated-reasoning_2005_35_contents .

A substantial amount of cyber security analyst time is spent handling well-known and na ve threats and policy violations on the local network. This includes both the time spent actually identifying and analyzing the activity as well as generating and filing reports associated with the activity. With increasing concern over advanced persistent threats, there is an interest in the development of techniques to automatically handle well-known threats and policy violations. We propose extensions to existing case-based reasoning approaches to support the unique requirements of cybersecurity report generation. Specifically, we consider the fact that we are reporting on hostile actors that will attempt to game the system or manipulate the system to actually aid the actors in obfuscating their activity. In this report, we describe the need for automated reporting, the applicability of case-based reasoning, our proposed extension to the standard case-based reasoning system model, and provide examples of the modified case-based reasoning system as applied to example cybersecurity scenarios.

The development and application of the Spacecraft Health Automated Reasoning Prototype (SHARP) for the operations of the telecommunications systems and link analysis functions in Voyager mission operations are presented. An overview is provided of the design and functional description of the SHARP system as it was applied to Voyager. Some of the current problems and motivations for automation in real-time mission operations are discussed, as are the specific solutions that SHARP provides. The application of SHARP to Voyager telecommunications had the goal of being a proof-of-capability demonstration of artificial intelligence as applied to the problem of real-time monitoring functions in planetary mission operations. AS part of achieving this central goal, the SHARP application effort was also required to address the issue of the design of an appropriate software system architecture for a ground-based, highly automated spacecraft monitoring system for mission operations, including methods for: (1) embedding a knowledge-based expert system for fault detection, isolation, and recovery within this architecture; (2) acquiring, managing, and fusing the multiple sources of information used by operations personnel; and (3) providing information-rich displays to human operators who need to exercise the capabilities of the automated system. In this regard, SHARP has provided an excellent example of how advanced artificial intelligence techniques can be smoothly integrated with a variety of conventionally programmed software modules, as well as guidance and solutions for many questions about automation in mission operations.

Several recent and fundamental advances have greatly increased the power of automated reasoning tools. Using these advances, Microsoft developed software such as Static Driver Verifier for finding bugs in device drivers. But automated reasoning libraries can be used in contexts beyond bug-finding. Examples include configuration management, scheduling, compilation, and other mathematics-based applications. In this talk I will provide information on the automated reasoning libraries that are currently available and describe how developers can use them to solve a wide variety of problems that require reasoning. I will also outline the projects within MSR to develop automated reasoning tools. ©2005 Microsoft Corporation. All rights reserved.

This talk describes how a combination of symbolic computation techniques with first-order theorem proving can be used for solving some challenges of automating program analysis, in particular for generating and proving properties about the logically complex parts of software. The talk will first present how computer algebra methods, such as Groebner basis computation, quantifier elimination and algebraic recurrence solving, help us in inferring properties of program loops with non-trivial arithmetic. Typical properties inferred by our work are loop invariants and expressions bounding the number of loop iterations. The talk will then describe our work to generate first-order properties of programs with unbounded data structures, such as arrays. For doing so, we use saturation-based first-order theorem proving and extend first-order provers with support for program analysis. Since program analysis requires reasoning in the combination of first-order theories of data structures, the talk also discusses new features in firstorder theorem proving, such as inductive reasoning and built-in boolean sort. These extensions allow us to express program properties directly in first-order logic and hence use further first-order theorem provers to reason about program properties.

Current automated approaches for compositional model checking in the assume-guarantee style are based on learning of assumptions as deterministic automata. We propose an alternative approach based on abstraction refinement. Our new method computes the assumptions for the assume-guarantee rules as conservative and not necessarily deterministic abstractions of some of the components, and refines those abstractions using counter-examples obtained from model checking them together with the other components. Our approach also exploits the alphabets of the interfaces between components and performs iterative refinement of those alphabets as well as of the abstractions. We show experimentally that our preliminary implementation of the proposed alternative achieves similar or better performance than a previous learning-based implementation.

Journal of Automated Reasoning 1989: Volume 5 , Issue Index. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_1988-12_4_4 . Next issue: sim_journal-of-automated-reasoning_1989-03_5_1 .

Journal of Automated Reasoning 1997: Volume 19 , Issue Index. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_1997-06_18_3 . Next issue: sim_journal-of-automated-reasoning_1997_19_contents .

Journal of Automated Reasoning 1997: Volume 19 , Issue Index. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_1997-06_18_3 . Next issue: sim_journal-of-automated-reasoning_1997_19_contents .

Journal of Automated Reasoning 1997: Volume 19 , Issue Index. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_1997-06_18_3 . Next issue: sim_journal-of-automated-reasoning_1997_19_contents .

In recent years, researchers in artificial intelligence have become interested in replicating human physical reasoning talents in computers. One of the most important skills in this area is predicting how physical systems will behave. This thesis discusses an implemented program that generates algebraic descriptions of how systems of rigid bodies evolve over time. Discussion about the design of this program identifies a physical reasoning paradigm and knowledge representation approach based on mathematical model construction and algebraic reasoning. This paradigm offers several advantages over methods that have become popular in the field, and seems promising for reasoning about a wide variety of classical mechanics problems. (AN)

The assurance of the safety or security of critical software rests on a clear understanding of the formal semantics of the programming language used. Operational semantics is the most widely used means of formally defining a language. The need for high levels of assurance, along with the complexity of these definitions for real programming languages, means that tool support is essential for carrying out reasoning about code with respect to the language definition. In this paper, we describe a generic approach to automated reasoning about the operational semantics of programming languages. As an application of this approach, we describe the construction of an environment for reasoning about programs written in a functional subset of ML. The system we describe (called Elle) captures the formal operational semantics definition of a large subset of Standard ML within the theorem prover Isabelle, and provides some support for the verification of ML programs. (AN)

Journal of Automated Reasoning 1990: Volume 6 , Issue Index. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_1989-12_5_4 . Next issue: sim_journal-of-automated-reasoning_1990_6_contents .

Journal of Automated Reasoning 1994: Volume 13 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_1994_13_index . Next issue: sim_journal-of-automated-reasoning_1994-08_13_1 .

Journal of Automated Reasoning 1995: Volume 14 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_1995_14_index . Next issue: sim_journal-of-automated-reasoning_1995-02_14_1 .

Journal of Automated Reasoning 1995: Volume 15 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_1995_15_index . Next issue: sim_journal-of-automated-reasoning_1995-08_15_1 .

Automated reasoning in classical logic has received much attention in the literature. Mature resolution theorem provers such as Vampire and E can handle enormous problems in first-order classical logic with equality. Waldmeister, a theorem prover for unit equational logic, has been incorporated into Mathematica as an equational reasoning method. Somewhat surprisingly, there has been much less attention devoted to non-classical logics. This is unfortunate, since many interesting and useful logics are inherently non-classical. Well known examples include intuitionistic, substructural and modal logics. Additionally, many modern logics for specialized tasks such as those designed for security and authentication protocols are non-classical as well. The inverse method is a generalization of resolution to non-classical logics. The polarized inverse method extends the inverse method with focusing and explicit polarity assignments that dramatically decrease the search space. In this talk we will suggest that the polarized inverse method provides an efficient and flexible framework for implementing theorem provers for non-classical logics. As evidence, we will demonstrate our recent theorem prover for intuitionistic logic, named Imogen. Imogen performs better than any other intuitionistic prover on standard benchmarks. We will also discuss recent work extending Imogen to handle domain-specific reasoning such as Microsoft's Infon logic. Finally, we will introduce a recent technique for encoding substructural logics into intuitionistic logic, thus yielding theorem provers for these logics 'for free'. ©2009 Microsoft Corporation. All rights reserved.

Nestan Tsiskaridze, University of California, Santa Barbara The modern world critically depends on the security and safety of software. We seek to ensure customer confidence and protect privacy, intellectual property, and national security. As threats to software security have become more sophisticated, so too have the techniques developed to ensure security. This talk focuses on novel opportunities to automate bug detection and security exploit generation provided by advances in symbolic execution and automated constraint solving. It discusses how symbolic execution can benefit from novel techniques in Satisfiability Modulo Theories (SMT), a subfield of automated theorem proving that in the past 10 years has revolutionized the discipline. The talk presents a recent highly successful application of SMT solvers in support of the security analysis of Web applications and how these new capabilities open opportunities for automating such analysis beyond the Web. This is a joint work with Clark Barrett (NYU/Stanford University), Morgan Deters (NYU), Tianyi Liang (The University of Iowa), Andrew Reynolds (The University of Iowa/EPFL), and Cesare Tinelli (The University of Iowa). Sign up to find out more about Enigma conferences: https://www.usenix.org/conference/enigma2017#signup Watch all Enigma 2017 videos at: http://enigma.usenix.org/youtube Source: https://www.youtube.com/watch?v=wLlnKu4HmaU Uploader: USENIX Enigma Conference Upload date: 2017-03-06

This volume, LNAI 13385, constitutes the refereed proceedings of the 11th International Joint Conference on Automated Reasoning, IJCAR 2022, held in Haifa, Israel, in August 2022. The 32 full research papers and 9 short papers presented together with two invited talks were carefully reviewed and selected from 85 submissions. The papers focus on the following topics: Satisfiability, SMT Solving,Arithmetic; Calculi and Orderings; Knowledge Representation and Jutsification; Choices, Invariance, Substitutions and Formalization; Modal Logics; Proofs System and Proofs Search; Evolution, Termination and Decision Prolems. This is an open access book.

Automated reasoning in classical logic has received much attention in the literature. Mature resolution theorem provers such as Vampire and E can handle enormous problems in first-order classical logic with equality. Waldmeister, a theorem prover for unit equational logic, has been incorporated into Mathematica as an equational reasoning method. Somewhat surprisingly, there has been much less attention devoted to non-classical logics. This is unfortunate, since many interesting and useful logics are inherently non-classical. Well known examples include intuitionistic, substructural and modal logics. Additionally, many modern logics for specialized tasks such as those designed for security and authentication protocols are non-classical as well. The inverse method is a generalization of resolution to non-classical logics. The polarized inverse method extends the inverse method with focusing and explicit polarity assignments that dramatically decrease the search space. In this talk we will suggest that the polarized inverse method provides an efficient and flexible framework for implementing theorem provers for non-classical logics. As evidence, we will demonstrate our recent theorem prover for intuitionistic logic, named Imogen. Imogen performs better than any other intuitionistic prover on standard benchmarks. We will also discuss recent work extending Imogen to handle domain-specific reasoning such as Microsoft's Infon logic. Finally, we will introduce a recent technique for encoding substructural logics into intuitionistic logic, thus yielding theorem provers for these logics 'for free'. ©2009 Microsoft Corporation. All rights reserved.

Journal of Automated Reasoning 1996: Volume 16 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_1996_16_index . Next issue: sim_journal-of-automated-reasoning_1996-03_16_1-2 .

Journal of Automated Reasoning 1997: Volume 19 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_1997_19_index . Next issue: sim_journal-of-automated-reasoning_1997-08_19_1 .

Journal of Automated Reasoning 2000: Volume 24 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_2000_24_index . Next issue: sim_journal-of-automated-reasoning_2000-02_24_1-2 .

Journal of Automated Reasoning 2002: Volume 29 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_2002_29_index . Next issue: sim_journal-of-automated-reasoning_2002_29_1 .

The planetary spacecraft mission OPS as applied to SHARP is studied. Knowledge systems involved in this study are detailed. SHARP development task and Voyager telecom link analysis were examined. It was concluded that artificial intelligence has a proven capability to deliver useful functions in a real time space flight operations environment. SHARP has precipitated major change in acceptance of automation at JPL. The potential payoff from automation using AI is substantial. SHARP, and other AI technology is being transferred into systems in development including mission operations automation, science data systems, and infrastructure applications.

Journal of Automated Reasoning 2005: Volume 34 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_2005_34_index . Next issue: sim_journal-of-automated-reasoning_2005_34_1 .

Journal of Automated Reasoning 1986: Volume 2 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_1986_2_index . Next issue: sim_journal-of-automated-reasoning_1986_2_1 .

Journal of Automated Reasoning 2004: Volume 33 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_2004_33_index . Next issue: sim_journal-of-automated-reasoning_2004_33_1 .

Journal of Automated Reasoning 2004: Volume 33 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_2004_33_index . Next issue: sim_journal-of-automated-reasoning_2004_33_1 .

This open access book constitutes the proceedings of the proceedings of the 32nd International Conference on Automated Reasoning with Analytic Tableaux and Related Methods, TABLEAUX 2023, held in Prague, Czech Republic, during September 18-21, 2023. The 20 full papers and 5 short papers included in this book together with 5 abstracts of invited talks were carefully reviewed and selected from 43 submissions. They present research on all aspects of the mechanization of reasoning with tableaux and related methods. The papers are organized in the following topical sections: tableau calculi; sequent calculi; theorem proving; non-wellfounded proofs; modal logics; linear logic and MV-algebras; separation logic; and first-order logics.

Journal of Automated Reasoning 1993: Volume 10 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_1993_10_index . Next issue: sim_journal-of-automated-reasoning_1993-02_10_1 .

Journal of Automated Reasoning 1993: Volume 10 , Issue CONTENTS. Digitized from IA1513825-03 . Previous issue: sim_journal-of-automated-reasoning_1993_10_index . Next issue: sim_journal-of-automated-reasoning_1993-02_10_1 .