Middle-out domain-specific aspect languages and their application in agent-based modelling runtime inspection

Domain-Specific Aspect Languages (DSALs) are a valuable tool for separating cross-cutting concerns, particularly within fields with endemic cross-cutting practices. Agent-Based Modelling (ABM) runtime inspection, which cuts across the core concern of model development, serves as a prime example. Despite their usefulness, DSALs face multiple adoption issues: the literature regarding their development and use is incohesive, coupling to a weave target hinders re-use, and available tooling is immature compared to Domain-Specific Languages (DSLs). We believe these issues can be aided by furthering DSL middle-out techniques for DSALs.We first define the background of what a DSAL is and how they may be used, moving onto how we can use DSL techniques to further DSALs. We develop a middle-out semantic model approach for developing domain-level DSALs with transparent aspect orientation using adaptions of DSL techniques. We have implemented the approach for model-specific DSALs for the in-house framework Animaux, and as middleware-specific DSAL for agent messages in the JADE framework, which can be specialised to models using extension DSALs. We give illustrative result cases using our implementations to provide a base of the user development costs and performance of this approach.In conclusion, we believe the adoption of these technologies aids ABM applications and encourage future work in similar fields. This thesis has given a base philosophy toward DSLs, a novel approach for the development of middle-out DSALs and illustrative cases of this approach

Applying agent technology to constructing flexible monitoring systems in process automation

The dissertation studies the application of agent technology to process automation monitoring and other domain specific functions. Motivation for the research work derives from the development of industrial production and process automation, and thereby the work load of operating personnel in charge of these large-scale processes has become more complex and difficult to handle. At the same time, the information technology infrastructure in process automation domain has developed ready to accept and utilise novel software engineering solutions. Agent technology is a new programming paradigm which has attractive properties like autonomy, flexibility and a possibility to distribute functions. In addition, agent technology offers a systematic methodology for designing goal based operations. This enables parts of the monitoring tasks to be delegated to the system. In this research, new agent system architecture is introduced. The architecture specifies a structure that enables the use of agents in the process monitoring domain. In addition, an introductory internal layered design of an agent aiming to combine Semantic Web and agent technologies is presented. The developed agent architecture is used in conjunction with the systematic agent design methodology to construct and implement four test cases. Each case has industrially motivated interest and illustrates various aspects of monitoring functionalities. These tests provide evidence that by utilising agent technology it is possible to develop new monitoring features for process operators, otherwise infeasible as such within current process automation systems. As a result of the research work, it can be stated that agent technology is a suited methodology to realise monitoring functionalities in process automation. It is also shown, that by applying solutions gained from the agent technology research, it is possible to define an architecture that enables to utilise the properties offered by agents in process automation environment. The proposed agent architecture supports features that are of generic interest in monitoring tasks. The developed architecture and research findings provide ground to import novel software engineering solutions to process automation monitoring

Coalition based approach for shop floor agility – a multiagent approach

Dissertation submitted for a PhD degree in Electrical Engineering, speciality of Robotics and Integrated Manufacturing from the Universidade Nova de Lisboa, Faculdade de Ciências e TecnologiaThis thesis addresses the problem of shop floor agility. In order to cope with the disturbances and uncertainties that characterise the current business scenarios faced by manufacturing companies, the capability of their shop floors needs to be improved quickly, such that these shop floors may be adapted, changed or become easily modifiable (shop floor reengineering). One of the critical elements in any shop floor reengineering process is the way the control/supervision architecture is changed or modified to accommodate for the new processes and equipment. This thesis, therefore, proposes an architecture to support the fast adaptation or changes in the control/supervision architecture. This architecture postulates that manufacturing systems are no more than compositions of modularised manufacturing components whose interactions when aggregated are governed by contractual mechanisms that favour configuration over reprogramming. A multiagent based reference architecture called Coalition Based Approach for Shop floor Agility – CoBASA, was created to support fast adaptation and changes of shop floor control architectures with minimal effort. The coalitions are composed of agentified manufacturing components (modules), whose relationships within the coalitions are governed by contracts that are configured whenever a coalition is established. Creating and changing a coalition do not involve programming effort because it only requires changes to the contract that regulates it

An intelligent system for facility management

A software system has been developed that monitors and interprets temporally changing (internal) building environments and generates related knowledge that can assist in facility management (FM) decision making. The use of the multi agent paradigm renders a system that delivers demonstrable rationality and is robust within the dynamic environment that it operates. Agent behaviour directed at working toward goals is rendered intelligent with semantic web technologies. The capture of semantics though formal expression to model the environment, adds a richness that the agents exploit to intelligently determine behaviours to satisfy goals that are flexible and adaptable. The agent goals are to generate knowledge about building space usage as well as environmental conditions by elaborating and combining near real time sensor data and information from conventional building models. Additionally further inferences are facilitated including those about wasted resources such as unnecessary lighting and heating for example. In contrast, current FM tools, lacking automatic synchronisation with the domain and rich semantic modelling, are limited to the simpler querying of manually maintained models.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

An intelligent system for facility management

A software system has been developed that monitors and interprets temporally changing (internal) building environments and generates related knowledge that can assist in facility management (FM) decision making. The use of the multi agent paradigm renders a system that delivers demonstrable rationality and is robust within the dynamic environment that it operates. Agent behaviour directed at working toward goals is rendered intelligent with semantic web technologies. The capture of semantics though formal expression to model the environment, adds a richness that the agents exploit to intelligently determine behaviours to satisfy goals that are flexible and adaptable. The agent goals are to generate knowledge about building space usage as well as environmental conditions by elaborating and combining near real time sensor data and information from conventional building models. Additionally further inferences are facilitated including those about wasted resources such as unnecessary lighting and heating for example. In contrast, current FM tools, lacking automatic synchronisation with the domain and rich semantic modelling, are limited to the simpler querying of manually maintained models

Proceedings of The Multi-Agent Logics, Languages, and Organisations Federated Workshops (MALLOW 2010)

http://ceur-ws.org/Vol-627/allproceedings.pdfInternational audienceMALLOW-2010 is a third edition of a series initiated in 2007 in Durham, and pursued in 2009 in Turin. The objective, as initially stated, is to "provide a venue where: the cost of participation was minimum; participants were able to attend various workshops, so fostering collaboration and cross-fertilization; there was a friendly atmosphere and plenty of time for networking, by maximizing the time participants spent together"

Investigation of an emotional virtual human modelling method

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In order to simulate virtual humans more realistically and enable them life-like behaviours, several exploration research on emotion calculation, synthetic perception, and decision making process have been discussed. A series of sub-modules have been designed and simulation results have been presented with discussion. A visual based synthetic perception system has been proposed in this thesis, which allows virtual humans to detect the surrounding virtual environment through a collision-based synthetic vision system. It enables autonomous virtual humans to change their emotion states according to stimuli in real time. The synthetic perception system also allows virtual humans to remember limited information within their own First-in-first-out short-term virtual memory. The new emotion generation method includes a novel hierarchical emotion structure and a group of emotion calculation equations, which enables virtual humans to perform emotionally in real-time according to their internal and external factors. Emotion calculation equations used in this research were derived from psychologic emotion measurements. Virtual humans can utilise the information in virtual memory and emotion calculation equations to generate their own numerical emotion states within the hierarchical emotion structure. Those emotion states are important internal references for virtual humans to adopt appropriate behaviours and also key cues for their decision making. The work introduces a dynamic emotional motion database structure for virtual human modelling. When developing realistic virtual human behaviours, lots of subjects were motion-captured whilst performing emotional motions with or without intent. The captured motions were endowed to virtual characters and implemented in different virtual scenarios to help evoke and verify design ideas, possible consequences of simulation (such as fire evacuation). This work also introduced simple heuristics theory into decision making process in order to make the virtual human’s decision making more like real human. Emotion values are proposed as a group of the key cues for decision making under the simple heuristic structures. A data interface which connects the emotion calculation and the decision making structure together has also been designed for the simulation system