Ivana Budinská

Production planning and scheduling by means of artificial immune systems and particle swarm optimisation algorithms

The main task of the scheduling optimisation process in production systems is to minimise production cost, overall production time and to ensure optimal utilisation of the resources. Application of stochastic search techniques to find a feasible schedule that minimise cost and satisfy all constraints jointed with all products can bring a particular solution of the complexity problem. On the other hand, the cost and the time of an optimisation process have to reciprocate with the found schedule; otherwise the optimisation loses its meaning. The article presents two stochastic methods, based on biologically inspired techniques, applied on a scheduling optimisation process. The first one is based on the mechanism inspired by biological evolution and the one method applies the swarm intelligence. The application of methods is illustrated on a real world example of a production line.

Robot Coordination Based on Biologically Inspired Methods

An embedded particle swarm optimization (PSO) technique combined with virtual pheromones deposition and rules for artificial bird flocking is proposed to handle an area coverage problem using a swarm of mobile robots. A simulation tool VERA that was developed to simulate a swarm behavior of a group of mobile agents is described. Results of simulation experiments and tests on Lego robots that prove the concept are presented. Results are discussed and future development is suggested in the end of the paper.

Task allocation within a heterogeneous multi-robot system

Multi robot systems have been extensively researched over past decades. Many open theoretical and practical problems, associated with them, are not solved in a sufficient level. The paper introduces an approach to solve a task allocation problem within a heterogeneous multi robot system. A formal representation of the problem is presented. A heuristic algorithm than can solve the problem, is introduced. Application possibilities of the presented solution are discussed in the paper, too.

Distributed Multi-agent System for Area Coverage Tasks: Architecture and Development

The article aims to present a new concept in mobile robotics – swarm robotics. It gives an overview of related research in coordination of mobile robots in a group and presents recent research activities in swarm robotics at the Institute of Informatics SAS. The architecture and development of a distributed multi-agent system for area coverage tasks are introduced.

Ontology driven administrative workflow management system with knowledge support

Abstract The paper describes an ontology approach to the modeling of administrative workflow processes. The ontological approach is applied on the RAPORT system. The RAPORT system is a light-weight system based on e-mail communication and internet technology. The description of architecture and basic principles of the RAPORT system is provided in this paper.

Case-Based Reasoning Applied for CAS-Decision System

Abstract This paper presents the CAS-Decision System, whose purpose is to assist the customers in choosing a method for modelling and designing the control system and simulation. Case-based reasoning is used to meet this purpose. We present two methods for searching and extracting the needed information.

SkyBat: A Swarm Robotic Model Inspired by Fission-Fusion Behaviour of Bats

An agent based model - SkyBat, based on long-term observation of bats behaviour under fission-fusion dynamics, is presented in this paper. The agents cooperate while searching for specific targets of interest in an unknown area. Although the agents are autonomous, they have an ability to move from one location to another without a group leader and to react to changes in environment.

Clustering analysis of online discussion participants.

Abstract In this paper we perform density-based clustering of discussion participants from online editions of two major Slovak national newspapers, Sme.sk and Cas.sk. We use language-independent statistical attributes characterising their communication patterns and the content of their posts. In each newspaper, we separately analyse two categories of news (domestic and international). A large majority of participants in each dataset was found to belong to one stable and dominant cluster present in all our datasets. We interpret it as comprising the “standard” or “average” discussion participants. The remaining participants could be viewed as various kinds of “anomalies” or “departures from normal” (not necessarily negative) and were assigned to several minor clusters. The shape and position of some minor clusters generalized well across the datasets. Overall, we found significant structural similarities between the four datasets in terms of histograms of attributes, the existence of one stable and dominant cluster, and the similar shape and location of several minor clusters. This is a significant result given that the four datasets were largely independent and the two newspapers adopted radically different policies for dealing with karma and foul language. The proposed approach therefore looks very promising as a means of identifying anomalous behaviour on diverse online discussion platforms.

Collaborative Learning Supported with Mediawiki Platform in Technical University Environment

According to several studies, student collaboration can be helpful in learning process. In this paper, we propose collaborative learning for students of a technical university as part of courses on “Computer criminality”. We have prepared a base platform, MediaWiki, to support the collaborative approach. The MediaWiki is a free open source platform originally used for Wikipedia. We also prepared a questionnaire for students about their opinion on using collaborative learning as part of the school courses. We assume, based on the responses given by the students, that they prefer knowledge sharing among other collaborative learning approaches. The paper summarizes findings about students’ attitude to collaborative learning and suggests some improvements for the design and development of a collaborative learning tool. A case study - a course on Computer criminality, is briefly described. Preliminary results indicate, that students can highly benefit from collaboration.

A Self-adapting Method for 3D Environment Exploration Inspired by Swarm Behaviour

A problem of finding an optimal size of a swarm of robots in a way of effective cooperation is not an easy task to solve. There are many factors, which influence the optimal size of the robotic swarm. Among major factors that have to be considered, belong communication, structure of environment and behavior of agents in the swarm. This paper presents a method for creating a decentralized self-adapting swarm of robots. The task is to set an optimal size of the swarm in a role of space exploration. Communication among robots is restricted to communication through the environment. The only way how agents communicate, is through artificial pheromone marks. This fact gives us an ability to create a decentralized algorithm for controlling and coordination of a robotic swarm, which is robust and efective.