Spatial Inference - Learning vs. Constraint Solving

Spatial Inference with Constraints

We present an approach for solving constraint nets occurring in spatial inference using methods of Machine Learning. In contrast to qualitative spatial reasoning we use a metric description. Relations between pairs of objects are represented by parameterised homogeneous transformation matrices and numerical (nonlinear) constraints on the parameters. For drawing inferences we have to multiply th...

SPATIAL INFERENCE AND CONSTRAINT SOLVING How to Depict Textual Spatial Descriptions from Internet

Today there are still many applications in the Internet, where the user is given a textual description of a spatial configuration (e.g. chat, e-mail or newsgroups). The user is asked to imagine the scene and to draw inferences. We present a new approach to generate depictions of such scenes. Besides of drawing spatial inferences, this leads to the problem of solving a system of complicated nume...

Application of Machine Learning Algorithms to Constraint Solving and Learning Logical Implications in Spatial Domains

Constraint learning using adaptive neural-fuzzy inference system

Purpose – The purpose of this paper is to present a new method for solving parametric programming problems; a new scheme of constraints fuzzification. In the proposed approach, constraints are learned based on deductive learning. Design/methodology/approach – Adaptive neural-fuzzy inference system (ANFIS) is used for constraint learning by generating input and output membership functions and su...

Extensions of Constraint Solving for Proof Planning Extensions of Constraint Solving for Proof Planning

The integration of constraint solvers into proof planning has pushed the problem solving horizon. Proof planning beneets from the general functionalities of a constraint solver such as consistency checks, constraint inference, as well as the search for instantiations. However, oo-the-shelf constraint solvers are usually geared towards their typical applications. Since proof planning diiers from...