Imagination in Technology. Innovative Freedom and Symbolic Constraints according to Gilbert Durand

2015 ◽  
pp. 159-171
Author(s):  
Jean-Jacques Wunenburger
Keyword(s):  
Symbolic Constraints

Les modèles de l’imaginaire issus de l’école française bachelardienne et durandienne ont permis de mieux appréhender l’étude des mythes, des religions et des arts. Non seulement les imaginaires obéissent à une logique symbolique, mais celle-ci s’enracine dans des soubassements corporels, comportementaux et même neurobiologiques, qui sont au cœur des neurosciences. Dans quelle mesure peut‑on transférer ces résultats de manière plus systématique aux milieux des artefacts techniques, et même aux nouvelles innovations technologiques aujourd’hui ? L’article tente de dégager quelques orientations programmatiques qui devraient permettre de comprendre combien la liberté d’innovation se conjugue avec des contraintes neuromotrices et symboliques.

scholarly journals JDart: Dynamic Symbolic Execution for Java Bytecode (Competition Contribution)

2020 ◽  
pp. 398-402 ◽  
Author(s):  
Malte Mues ◽  
Falk Howar
Keyword(s):  
Symbolic Execution ◽  
Model Checker ◽  
Constraint Solver ◽  
Java Bytecode ◽  
Software Model ◽  
Dynamic Symbolic Execution ◽  
Symbolic Constraints

Abstract JDart performs dynamic symbolic execution of Java programs: it executes programs with concrete inputs while recording symbolic constraints on executed program paths. A constraint solver is then used for generating new concrete values from recorded constraints that drive execution along previously unexplored paths. JDart is built on top of the Java PathFinder software model checker and uses the JConstraints library for the integration of constraint solvers.

Symbolic Computation of Inverse Kinematics for General 6R Manipulators Based on Raghavan and Roth’s Solution

2020 ◽  
Author(s):  
Keisuke Arikawa
Keyword(s):  
Characteristic Polynomial ◽  
Symbolic Computation ◽  
Inverse Kinematics ◽  
Structural Parameters ◽  
Efficient Computation ◽  
Joint Angles ◽  
Arbitrary Geometries ◽  
The Matrix ◽  
Rational Polynomials ◽  
Symbolic Constraints

Abstract We discuss the symbolic computation of inverse kinematics for serial 6R manipulators with arbitrary geometries (general 6R manipulators) based on Raghavan and Roth’s solution. The elements of the matrices required in the solution were symbolically calculated. In the symbolic computation, an algorithm for simplifying polynomials upon considering the symbolic constraints (constraints of the trigonometric functions and those of the rotation matrix), a method for symbolic elimination of the joint variables, and an efficient computation of the rational polynomials are presented. The elements of the matrix whose determinant produces a 16th-order single variable polynomial (characteristic polynomial) were symbolically calculated by using structural parameters (parameters that define the geometry of the manipulator) and hand configuration parameters (parameters that define the hand configuration). The symbolic determinant of the matrix consists of huge number of terms even when each element is replaced by a single symbol. Instead of expressing the coefficients in a characteristic polynomial by structural parameters and hand configuration parameters, we substituted appropriate rational numbers that strictly satisfy the constraints of the symbols for the elements of the matrix and calculated the determinant (numerical error free calculation). By numerically calculating the real roots of the rational characteristic polynomial and the joint angles for each root, we verified the formulation for the symbolic computation.

scholarly journals Paramodulation with Built-in AC-Theories and Symbolic Constraints

1997 ◽  
Vol 23 (1) ◽  
pp. 1-21 ◽  
Author(s):  
ROBERT NIEUWENHUIS ◽  
ALBERT RUBIO
Keyword(s):  
Symbolic Constraints

scholarly journals SCIL — Symbolic Constraints in Integer Linear Programming

2002 ◽  
pp. 75-87 ◽  
Author(s):  
Ernst Althaus ◽  
Alexander Bockmayr ◽  
Matthias Elf ◽  
Michael Jünger ◽  
Thomas Kasper ◽  
...  
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Symbolic Constraints

scholarly journals Property-Directed Inference of Relational Invariants

2019 ◽  
Vol 26 (4) ◽  
pp. 550-571
Author(s):  
Dmitry A. Mordvinov
Keyword(s):  
Experimental Evaluation ◽  
Horn Clauses ◽  
Non Linear ◽  
Symbolic Constraints ◽  
Novel Algorithm

Property Directed Reachability (PDR) is an efficient and scalable approach to solving systems of symbolic constraints also known as Constrained Horn Clauses (CHC). In the case of non-linear CHCs, which may arise, e.g., from relational verification tasks, PDR aims to infer an inductive invariant for each uninterpreted predicate. However, in many practical cases this reasoning is not successful, as invariants should be derived for groups of predicates instead of individual predicates. The article describes a novel algorithm that identifies these groups automatically and complements the existing PDR technique. The key feature of the algorithm is that it does not require a possibly expensive synchronization transformation over the system of CHCs. We have implemented the algorithm on top of a up-to-date CHC solver Spacer. Our experimental evaluation shows that for some CHC systems, on which existing solvers diverge, our tool is able to discover relational invariants.

scholarly journals Cost Problems for Parametric Time Petri Nets*

2022 ◽  
Vol 183 (1-2) ◽  
pp. 97-123
Author(s):  
Didier Lime ◽  
Olivier H. Roux ◽  
Charlotte Seidner
Keyword(s):  
Petri Nets ◽  
Software Tool ◽  
Convex Polyhedra ◽  
Time Constraints ◽  
Time Petri Nets ◽  
Parameter Synthesis ◽  
Mere Existence ◽  
Parameter Values ◽  
Explicit Enumeration ◽  
Symbolic Constraints

We investigate the problem of parameter synthesis for time Petri nets with a cost variable that evolves both continuously with time, and discretely when firing transitions. More precisely, parameters are rational symbolic constants used for time constraints on the firing of transitions and we want to synthesise all their values such that some marking is reachable, with a cost that is either minimal or simply less than a given bound. We first prove that the mere existence of values for the parameters such that the latter property holds is undecidable. We nonetheless provide symbolic semi-algorithms for the two synthesis problems and we prove them both sound and complete when they terminate. We also show how to modify them for the case when parameter values are integers. Finally, we prove that these modified versions terminate if parameters are bounded. While this is to be expected since there are now only a finite number of possible parameter values, our algorithms are symbolic and thus avoid an explicit enumeration of all those values. Furthermore, the results are symbolic constraints representing finite unions of convex polyhedra that are easily amenable to further analysis through linear programming. We finally report on the implementation of the approach in Romeo, a software tool for the analysis of time Petri nets.

scholarly journals JDart: Portfolio Solving, Breadth-First Search and SMT-Lib Strings (Competition Contribution)

2021 ◽  
pp. 448-452
Author(s):  
Malte Mues ◽  
Falk Howar
Keyword(s):  
String Theory ◽  
Symbolic Execution ◽  
Constraint Solving ◽  
Breadth First Search ◽  
Dynamic Symbolic Execution ◽  
Symbolic Constraints

AbstractJDartperforms dynamic symbolic execution ofJavaprograms: it executes programs with concrete inputs while recording symbolic constraints on executed program paths. A portfolio of constraint solvers is then used for generating new concrete values from recorded constraints that drive execution along previously unexplored paths. For SV-COMP 2021, we improvedJDartby implementing exploration strategies, bounded analysis, and path-specific constraint solving strategies, as well as by enabling the use of SMT-Lib string theory for encoding of string operations.

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