Dennis Jarvis

Achieving holonic control: an incremental approach

Holonic manufacturing is a concept of considerable promise in terms of providing the flexibility and responsiveness required by virtual enterprises. However if this promise is to be realised then two key issues need to be addressed. Firstly, migration strategies need to be developed to enable existing manufacturing systems which use conventional controller technology to progressively incorporate holonic manufacturing concepts. Secondly, holonic manufacturing principles need to be applied and integrated at all levels of the production planning and control process. In this paper, our primary concern is the first issue--we present and evaluate the technical feasibility of a strategy for the incremental introduction of holonic manufacturing principles into existing production control systems. We believe that the approach that we present, through its adoption of a strong part and task execution focus, will provide a sound platform for addressing the second issue.

Holonic Execution: A BDI Approach

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Holonic Diagnosis for an Automotive Assembly Line

Diagnosis is an important function of a holonic manufacturing system if the desired levels of stability, adaptability and flexibility are to be achieved. Our research agenda is to study holonic behaviours (such as diagnosis and control) through the incorporation of these behaviours into operational industrial systems. Given the lack of fielded holonic solutions in industry, we are currently constrained to use conventional systems in our work. In this paper we describe the development of a holonic diagnostic capability for a PLC-controlled vehicle assembly line. A novel model-based strategy is used for diagnosis. Because of the constraints imposed on model formation in this environment, a two-phase approach consisting of off-line fault space generation and online fault space analysis is used. The fault space analysis utilises heuristics to achieve the desired performance levels (diagnosis in less than 60 seconds and success rates of greater than 90%). Areas for further research in holonic diagnosis are identified.

Multiagent Systems and Applications

Since its conception almost 30 years ago, the BDI (Belief Desire Intention) model of agency has become established, along with Soar, as the approach of choice for practitioners in the development of knowledge intensive agent applications. However, in developing BDI agent applications for over 15 years, the authors of this book have observed a disconnect between what the BDI model provides and what is actually required of an agent model in order to build practical systems. The GORITE BDI framework was developed to address this gap and this book is written for students, researchers and practitioners who wish to gain a practical understanding of how GORITE is used to develop BDI agent applications. In this regard, a feature of the book is the use of complete, annotated examples. As GORITE is a Java framework, a familiarity with Java (or a similar language) is assumed, but no prior knowledge of the BDI model is required.

Prospects of solar energy in Australia

Today, more than 80% of energy is produced from fossil fuels that pollute the air and surrounding environments each and every day, creating global warming. Therefore it is time to think about alternative sources of energy to build a climate friendly environment. In contrast to fossil fuels, renewable energy offers alternative sources of energy which are in general pollution free, unlimited, and environmentally sustainable. This paper presents a feasibility study undertaken to investigate the prospects of solar energy for the climate similar to Australia so as to further investigate the impacts of renewable energy sources in existing and future smart power systems. The monthly average global solar radiation has been collected for twenty-one locations in Australia from the National Aeronautics and Space Administration (NASA). Hybrid Optimisation Model for Electric Renewable (HOMER), and Renewable-energy and Energy-efficient Technologies (RETScreen) computer tools were used to perform comparative analysis of solar energy with diesel and hybrid systems. Initially, total net present cost (NPC), cost of energy (COE) and the renewable fraction (RF) were measured as performances metrics to compare the performances of different systems. For better optimisation, the model has been refined with a sensitivity analysis which explores performance variations due to solar irradiation and electricity prices. Finally, a statistical analysis was conducted to select the best potential places in Australia that produce maximum solar energy.

Teams in Multi-Agent Systems

Multi-agent systems involve agents interacting with each other and the environment and working to achieve individual and group goals. The achievement of group goals requires that agents work together within teams. In this paper we first introduce three philosophical approaches that result from different answers to two key questions. Secondly we consider three theoretical frameworks for modelling team behaviour. Next we look at two agent implementation models. Finally, we consider one of those implementation models — JACK Teams — and place it in the context of the philosophical debate and the theoretical frameworks.

Multi-Agent Systems

Intelligent agent technology is at an intriguing stage in its development. Commercial strength agent applications are increasingly being developed in domains as diverse as manufacturing (Deen, 2003; Bussman et al., 2004; Jarvis et al., 2008a) war gaming (Jones et al., 1999; Heinze et al., 2002) and UAV mission management (Karim and Heinze, 2005). Furthermore industrial strength development environments are available, e.g. (AOS Group, 2012; University of Michigan, 2012; JADE, 2012) and design methodologies (Padgham and Winikoff, 2004) reference architectures (van Brussel et al., 1998) and standards (IEEE Computer Society, 2012) are beginning to appear.

Using agent teams to model enterprise behaviour

Service Oriented Architectures have enabled enterprise architectures to be composed as loosely coupled collections of applications that interact using platform independent web services and standards. Enterprise behaviour is then traditionally modelled as workflows, with business requests invoking specific enterprise services. In this paper, we propose an alternative approach, where enterprise behaviour is modelled as goals to be achieved by dynamically formed teams. These teams can be formed within an individual enterprise or can span enterprises, thus enabling virtual enterprises to be explicitly modelled. Team behaviours are specified independently of the actual services that are available, thus providing a clear separation between behaviour specification (business process definition) and behaviour execution (business process operation). The team modelling framework that is used is JACK™ Teams, which is a component of the JACK™ Intelligent Agents product suite [1].

Special issue: Innovations in intelligent agent technology

Ajith Abraham, Dennis Jarvis, Jacquie Jarvis and Lakhmi Jain aNorwegian Center of Excellence for Quantifiable Quality of Service, Norwegian University of Science and Technology, O.S. Bragstads plass 2E, N-7491 Trondheim Norway E-mail: ajith.abraham@ieee.org bCentre for Intelligent and Networked Systems, CQ University Australia, Rockhampton, Queensland 4702, Australia E-mail: d.jarvis@cqu.edu.au; j.jarvis@cqu.edu.au cProfessor of Knowledge-Based Engineering, Founding Director of the KES Centre, School of Electrical and Information Engineering, University of South Australia, Mawson Lakes, South Australia 5095, Australia E-mail: lakhmi.jain@unisa.edu.au

Interoperability with Goal Oriented Teams (GORITE)

We look at interoperability with Goal Oriented Teams modelling, which includes an outsourcing paradigm as the means by which to link separate Business Processes. Although the framework proposes the Team Programming perspective for Business Process modelling, it also supports the notion that a role filler achieves its goals by outsourcing to an external Business Process model. The core capability, RemoteCoaching, provides the required separation between the Business Process model at intentional level and the interfacing technology that facilitates the actual connection to the external Business Process model. Following the Service Oriented Architecture (SOA) principles, the outsourcing sub system is generalised to avoid practical constraints on the remote technology base, i.e., the remote Business Process model might be another Goal Oriented Teams (GORITE) model, or based on some other framework.