Adam Meissner

Multi-agent blackboard architecture for a mobile robot

In the paper, the architecture of a mobile robot cooperating with other robots and some stationary devices in a task of collective perception and world modelling is considered. We analyze data-driven processing of information performed by an individual robot treated as an agent and we propose to organize it as a set of experts (also treated as agents) exchanging data by means of a blackboard. We analyze functions performed by the blackboard agents and present results of preliminary experiments with real robots.

Experimental analysis of some computation rules in a simple parallel reasoning system for the ALC description logic

Experimental analysis of some computation rules in a simple parallel reasoning system for the ALC description logic A computation rule determines the order of selecting premises during an inference process. In this paper we empirically analyse three particular computation rules in a tableau-based, parallel reasoning system for the ALC description logic, which is built in the relational programming model in the Oz language. The system is constructed in the lean deduction style, namely, it has the form of a small program containing only basic mechanisms, which assure soundness and completeness of reasoning. In consequence, the system can act as a convenient test-bed for comparing various inference algorithms and their elements. We take advantage of this property and evaluate the studied methods of selecting premises with regard to their efficiency and speedup, which can be obtained by parallel processing.

A Simple Parallel Reasoning System for the

In this paper we present a simple, tableau-based, parallel reasoning system for the

\mathcal{ALC}

\mathcal{ALC}

Description Logic

description logic. The system is built in relational model in the Oz language and has a form of a short program comprising the implementation of tableau rules. The program can be executed according to various strategies, particularly in parallel on distributed machines. For this purpose, we use a parallel search engine available in the Mozart environment. We describe results of experiments for estimating the speedup obtained by parallel processing.

Reasoning about XML schema mappings in the presence of key constraints and value dependencies

Schema mappings play a central role in both data integration and data exchange, and are understood as high-level specifications describing the relationships between data schemas. Based on these specifications, data structured under a source schema can be transformed into data structured under a target schema. During the transformation some structural constraints, both context-free (the structure) and contextual (e.g. keys and value dependencies) should be taken into account. In this work, we present a new formalism for the schema mapping specification. We propose a new class of tree-pattern formulas in order to extend semantics of XML schema mappings by specification of key constraints and value dependencies. We discuss foundations of the method and propose a key-preserving transformation algorithm.

Computing an irregularity strength of selected graphs

Abstract In this paper we describe how the problem of computing an irregularity strength of a graph may be expressed and solved in terms of constraint programming over finite domains, i.e. CP(FD). We also present some theoretical and experimental results concerning an irregularity strength computed for cubic graphs and K n − e graphs. Additionally, we give some remarks on the implementation of our approach in the Oz programming language on the platform of the Mozart system.

A simple distributed reasoning system for the connection calculus

We present a simple, distributed reasoning system for the first order logic, which applies a connection calculus as an inference method. The calculus has been proposed by Bibel as a generalization of some other popular approaches, like the tableau calculus or the resolution-based inference. The system is constructed in a lean deduction style and it has been inspired to some extent by a sequential reasoner leanCoP, implemented in Prolog. Our reasoner has a form of a relational program in the Oz language. In this programming model, a computational strategy is a parameter of a program having a form of a special object called a search engine. Therefore, the same program can be run in various ways, particularly in parallel on distributed machines. For this purpose, we use a parallel search engine available on the Mozart platform, which is a programming environment for Oz. We also describe results of experiments for estimating a speedup obtained by the distributed processing.

Vertex-Magic total labeling of a graph by distributed constraint solving in the mozart system

In this paper we present how a problem of a vertex-magic total labeling of a graph may be expressed in terms of constraint programming over finite domains (CP(FD)) in the Mozart system. A program representing the problem is easily transformable into a parallel version, which can be executed on distributed machines. We describe the results of experiments for estimating a speedup, a work granularity and an overhead of a parallel version in comparison with sequential computations.

Introducing Parallel Computations to a PTTP-Based First-Order Reasoning Process in the Oz Language

We present a method of adding parallel computations to a reasoning process based on the Prolog Technology Theorem Proving approach. For this purpose, the input set of first-order logic formulas is translated into a logically equivalent program in the Oz language.