Intelligent agent for formal modelling of temporal multi-agent systems

Software systems are becoming complex and dynamic with the passage of time, and to provide better fault tolerance and resource management they need to have the ability of self-adaptation. Multi-agent systems paradigm is an active area of research for modeling real-time systems. In this research, we have proposed a new agent named SA-ARTIS-agent, which is designed to work in hard real-time temporal constraints with the ability of self-adaptation. This agent can be used for the formal modeling of any self-adaptive real-time multi-agent system. Our agent integrates the MAPE-K feedback loop with ARTIS agent for the provision of self-adaptation. For an unambiguous description, we formally specify our SA-ARTIS-agent using Time-Communicating Object-Z (TCOZ) language. The objective of this research is to provide an intelligent agent with self-adaptive abilities for the execution of tasks with temporal constraints. Previous works in this domain have used Z language which is not expressive to model the distributed communication process of agents. The novelty of our work is that we specified the non-terminating behavior of agents using active class concept of TCOZ and expressed the distributed communication among agents. For communication between active entities, channel communication mechanism of TCOZ is utilized. We demonstrate the effectiveness of the proposed agent using a real-time case study of traffic monitoring system

Zero-gravity movement studies

The use of computer graphics to simulate the movement of articulated animals and mechanisms has a number of uses ranging over many fields. Human motion simulation systems can be useful in education, medicine, anatomy, physiology, and dance. In biomechanics, computer displays help to understand and analyze performance. Simulations can be used to help understand the effect of external or internal forces. Similarly, zero-gravity simulation systems should provide a means of designing and exploring the capabilities of hypothetical zero-gravity situations before actually carrying out such actions. The advantage of using a simulation of the motion is that one can experiment with variations of a maneuver before attempting to teach it to an individual. The zero-gravity motion simulation problem can be divided into two broad areas: human movement and behavior in zero-gravity, and simulation of articulated mechanisms

Socionic Multi-Agent Systems Based on Reflexive Petri Nets and Theories of Social Self-Organisation

This contribution summarises the core results of the transdisciplinary ASKO project, part of the German DFG's programme Sozionik, which combines sociologists' and computer scientists' skills in order to create improved theories and models of artificial societies. Our research group has (a) formulated a social theory, which is able to explain fundamental mechanisms of self-organisation in both natural and artificial societies, (b) modelled this in a mathematical way using a visual formalism, and (c) developed a novel multi-agent system architecture which is conceptually coherent, recursively structured (hence non-eclectic) and based on our social theory. The article presents an outline of both a sociological middle-range theory of social self-organisation in educational institutions, its formal, Petri net based model, including a simulation of one of its main mechanisms, and the multi-agent system architecture SONAR. It describes how the theory was created by a re-analysis of some grand social theories, by grounding it empirically, and finally how the theory was evaluated by modelling its concepts and statements.Multi-Agents Systems, Petri Nets, Self-Organisation, Social Theories

COACHES Cooperative Autonomous Robots in Complex and Human Populated Environments

Public spaces in large cities are increasingly becoming complex and unwelcoming environments. Public spaces progressively become more hostile and unpleasant to use because of the overcrowding and complex information in signboards. It is in the interest of cities to make their public spaces easier to use, friendlier to visitors and safer to increasing elderly population and to citizens with disabilities. Meanwhile, we observe, in the last decade a tremendous progress in the development of robots in dynamic, complex and uncertain environments. The new challenge for the near future is to deploy a network of robots in public spaces to accomplish services that can help humans. Inspired by the aforementioned challenges, COACHES project addresses fundamental issues related to the design of a robust system of self-directed autonomous robots with high-level skills of environment modelling and scene understanding, distributed autonomous decision-making, short-term interacting with humans and robust and safe navigation in overcrowding spaces. To this end, COACHES will provide an integrated solution to new challenges on: (1) a knowledge-based representation of the environment, (2) human activities and needs estimation using Markov and Bayesian techniques, (3) distributed decision-making under uncertainty to collectively plan activities of assistance, guidance and delivery tasks using Decentralized Partially Observable Markov Decision Processes with efficient algorithms to improve their scalability and (4) a multi-modal and short-term human-robot interaction to exchange information and requests. COACHES project will provide a modular architecture to be integrated in real robots. We deploy COACHES at Caen city in a mall called “Rive de l’orne”. COACHES is a cooperative system consisting of ?xed cameras and the mobile robots. The ?xed cameras can do object detection, tracking and abnormal events detection (objects or behaviour). The robots combine these information with the ones perceived via their own sensor, to provide information through its multi-modal interface, guide people to their destinations, show tramway stations and transport goods for elderly people, etc.... The COACHES robots will use different modalities (speech and displayed information) to interact with the mall visitors, shopkeepers and mall managers. The project has enlisted an important an end-user (Caen la mer) providing the scenarios where the COACHES robots and systems will be deployed, and gather together universities with complementary competences from cognitive systems (SU), robust image/video processing (VUB, UNICAEN), and semantic scene analysis and understanding (VUB), Collective decision-making using decentralized partially observable Markov Decision Processes and multi-agent planning (UNICAEN, Sapienza), multi-modal and short-term human-robot interaction (Sapienza, UNICAEN

An agile and adaptive holonic architecture for manufacturing control

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. 2004. Faculdade de Engenharia. Universidade do Port

Agent and cyber-physical system based self-organizing and self-adaptive intelligent shopfloor

The increasing demand of customized production results in huge challenges to the traditional manufacturing systems. In order to allocate resources timely according to the production requirements and to reduce disturbances, a framework for the future intelligent shopfloor is proposed in this paper. The framework consists of three primary models, namely the model of smart machine agent, the self-organizing model, and the self-adaptive model. A cyber-physical system for manufacturing shopfloor based on the multiagent technology is developed to realize the above-mentioned function models. Gray relational analysis and the hierarchy conflict resolution methods were applied to achieve the self-organizing and self-adaptive capabilities, thereby improving the reconfigurability and responsiveness of the shopfloor. A prototype system is developed, which has the adequate flexibility and robustness to configure resources and to deal with disturbances effectively. This research provides a feasible method for designing an autonomous factory with exception-handling capabilities

Process control and configuration of a reconfigurable production system using a multi-agent software system

Thesis (M. Tech. (Information Technology)) -- Central University of technology, Free State, 2011Traditional designs for component-handling platforms are rigidly linked to the product being produced. Control and monitoring methods for these platforms consist of various proprietary hardware controllers containing the control logic for the production process. Should the configuration of the component handling platform change, the controllers need to be taken offline and reprogrammed to take the changes into account. The current thinking in component-handling system design is the notion of re-configurability. Reconfigurability means that with minimum or no downtime the system can be adapted to produce another product type or overcome a device failure. The re-configurable component handling platform is built-up from groups of independent devices. These groups or cells are each responsible for some aspect of the overall production process. By moving or swopping different versions of these cells within the component-handling platform, re-configurability is achieved. Such a dynamic system requires a flexible communications platform and high-level software control architecture to accommodate the reconfigurable nature of the system. This work represents the design and testing of the core of a re-configurable production control software platform. Multiple software components work together to control and monitor a re-configurable component handling platform. The design and implementation of a production database, production ontology, communications architecture and the core multi-agent control application linking all these components together is presented

A distributed knowledge-based approach to flexible automation : the contract-net framework

Includes bibliographical references (p. 26-29)