Symbolic transducers extend classical finite state transducers to infinite or large alphabets like Unicode, and are a popular tool in areas requiring reasoning over string transformations where traditional techniques do not scale. Here we develop the theory for and an algorithm for computing quotients of such transducers under indistinguishability preserving equivalence relations over states su...

This paper presents some of the benefits of a general purpose symbolic computation environment when constructing and generating simulation code for multibody, multidomain systems. Specifically, it considers how tools provided by these environments can be harnessed to generate highly efficient simulation code. MapleSim, a modeling and simulation platform that is based on the Maple symbolic compu...

Agent programming is mostly a symbolic discipline and, as such, draws little benefits from probabilistic areas as machine learning and graphical models. However, the greatest objective of agent research is the achievement of autonomy in dynamical and complex environments — a goal that implies embracing uncertainty and therefore the entailed representations, algorithms and techniques. This paper...

This paper studies the solving of finite-domain action planning problems with discrete action costs and soft constraints. For sequential optimal planning, a symbolic perimeter database heuristic is addressed in a bucket implementation of A*. For computing net-benefits, we propose symbolic branch-and-bound search together with some search refinements. The net-benefit we optimize is the total ben...

we need sociology theories, for that understand of sociology and politic problems. french sociologist pierre bourdieu's theory practice and symbolic power are our best resource; for understanding social and political fields. this article reviews the language and symbolic power; indicating its function in social and political fields. we need sociology theories, for that understand of sociol...

This work concentrates on three different modifications of a genetic programming system for symbolic regression analysis. The coefficient of correlation R is used as fitness function instead of the mean squared error and offspring selection is used to ensure a steady improvement of the achieved solutions. Additionally, as the fitness evaluation consumes most of the execution time, the generated...

Combining task and motion planning requires to interleave causal and geometric reasoning, in order to guarantee the plan to be executable in the real world. The resulting search space, which is the cross product of the symbolic search space and the geometric search space, is huge. Systematically calling a geometric reasoner while evaluating symbolic actions is costly. On the other hand, geometr...

The environmental benefits of deliberative democracy are increasingly cited, but not well understood. Nor are the processes involved in arriving at deliberated policy preferences in contrast to those under the status quo. Analysis of the Far North Queensland Citizens’ Jury (FNQCJ) reveals that the difference reflects as much a move away from a non-deliberative status quo as toward a deliberativ...

Recently, search based techniques have received great attention as a means of automating the test data generation activity. On the contrary, more traditional methods that automate the test data generation usually employ symbolic execution by incorporating a path generation phase and constraint solvers to produce the sought test data. In this paper, the benefits of both schools of thought are br...

We extend recent approaches for calculating the probability of program behaviors, to allow model counting for complex data structures with numeric fields. We use symbolic execution with lazy initialization to compute the input structures leading to the occurrence of a target event, while keeping a symbolic representation of the constraints on the numeric data. Off-the-shelf model counting tools...