Clinton Heinze

Flying Together: Modelling Air Mission Teams

The problem of modelling air missions is part of a larger problem—simulating possible war-like scenarios in the air, sea, and on land. In modelling such military systems one is required to model the behaviour of various actors and the resources that are available to them. One aspect of this problem is the modelling of a group of actors as a team and then modelling the coordinated behaviour of such a team to achieve a joint goal.In the domain of air mission modelling the actors are pilots who control aircraft and their behaviour is referred to as tactics. In this paper we present the approach we adopted in modelling teams and team tactics as part of the development of the Smart Whole AiR Mission Model (SWARMM) for the Air Operations Division of the Australian Defence Science and Technology Organization. In our approach teams are composed of sub-teams and adopt organizational structures. Such structures define the responsibilities of the sub-teams towards the mission to be achieved as well as towards the control and coordination of the sub-teams. We also describe how communication is used when adopting a variety of control and coordination strategies and how one could reason about the choice of organizational structures for a given mission and situation.

Extending the UML for designing Jack agents

Mainstreaming and industrialising agent technologies requires suitable methodological and technological support for the various engineering activities associated with managing the complexity of any software system development. Despite its origins in object oriented software engineering the UML provides a rich and extensible set of modelling constructs that can be applied to agent oriented technologies. This paper provides details of extensions to the UML for the design of agents that are to be implemented in the JACK language. These extensions provide the capacity to model the behaviour of agents for the purposes of design and, though the extensions are language specific, future generalisation and application to other agent languages can be supported as a industry-wide consensus about the nature of agency emerges over the next few years. This research builds on previously proposed extensions to the UML and moves a step closer to the goal of providing through-life engineering support to agent oriented systems development. This work is motivated by a pressing need to maintain, modify, develop and deploy existing and future agent based simulations of military operations for the Australian Defence Force.

Specifying Agent Behaviour with Use Cases

The software engineering of multi-agent systems demands specification of the required agent behaviours to provide documented requirements for the design and implementation phases. A methodology for the analysis and specification of agent behaviours is proposed, which arises from a lengthy experience in the construction of multi-agent simulations for military operations research. The methodology builds upon the existing use case modelling techniques provided by the Unified Modeling Language (UML) and is in keeping with the agent extensions to the UML proposed elsewhere. A case-study from a specific multi-agent air combat simulation accompanies the elaboration of the methodology.

Thinking Quickly: Agents for Modeling Air Warfare

Within Air Operations Division of DSTO intelligent agents are used to model the tactical decision making processes of pilots and fighter-controllers involved in air combat. One of the largest hurdles to be overcome by software engineers and analysts, when developing simulations of the air defence environment, is the acquisition of domain knowledge. Primarily the source of this knowledge is the pilots and other operational personnel, whose availability is limited and who have little experience with the design or development of simulation software. The adoption of agent oriented technologies has realized a number of significant benefits. High amongst these is the ability for operational air force personnel to become actively involved in the modification, design and development of these simulations. This involvement has dramatically reduced the time taken to prototype, test, and commission software and has resulted in simulations that have the confidence of the RAAF.

RescueModel: A Multi-Agent Simulation of Bushfire Disaster Management

The RescueModel project is a vehicle for research into multiagent systems, architectures, and strategies. It builds on the theoretical, practical, and experimental base of a decade of beliefs-desires-intentions (BDI) agent systems development. This paper describes a project that will bring together the environmental richness found usually in large scale military operations research simulations with the architectural richness of agent models often researched in universities. Proposed applications of RescueModel include search and rescue and disaster response studies.

Using the UML to model knowledge in agent systems

The UML has been used to model the knowledge required to engineer agent systems. The UML provides mechanisms for modelling the knowledge about a domain, partitioning the knowledge into appropriate packages and providing a means of moving from analysis to design. This paper argues that the UML is a suitable language for knowledge modelling in agent systems and provides details of the techniques and extensions employed. By modifying and applying commonly used mainstream modelling languages such as the UML tool and methodology support for the construction of agent systems can be leveraged from existing practices.

Enabling perception for plan recognition in multi-agent air mission simulations

The potential synergy between instance-based pattern recognition and means-end (possible world) reasoning is explored for supporting plan recognition in multi-aeroplane air-mission simulations. A means-end-reasoning model is then used to deliberate about and invoke standard operating procedures, based on recognised activity. The reasoning model constrains the recognition process by framing queries according to what a pilot would expect during the execution of the current plant(s). The importance of capturing relative information in these multi-agent simulations is emphasised, including self-aeroplane, aeroplane-aeroplane and aeroplane-environment relationships.

Towards reuse in agent oriented information systems: the importance of being purposive

The emergence of large information systems has pushed software specification into the area of business modelling to adequately capture and consider business requirements. At the same time, there has been a move toward techniques for specifying the behaviours of and the knowledge associated with intelligent agents as these are increasingly found as important components of those information systems. This paper presents four software models useful for specifying the requirements of an agent oriented information system. Adopting a similar notation for each model smooths the transition between models. It will be shown that it is in the relationships between these models there is scope for capturing purposive descriptions that facilitate reuse at various levels. A commentary on the importance of an explicit representation of the purpose for which a software component is intended is provided followed by an example, from the domain of military simulation, that illustrates the model and its application. The aim of this paper is to present a modelling approach that unifies business models, use case models, agent behavioural models and domain models, for the purpose of specifying an agent oriented information system.

What Is an Agent and Why Should I Care

A range of agent implementation technologies are reviewed according to five user-based criteria and via a comparison with object-oriented programming. The comparison with OO shows that some parts of object technology are a candidate implementation technique for some parts of agent systems. However, many other non-object-based implementation techniques may be just as useful. Also, for agents with mentalistic attitudes, the high-level specification of agent behavior requires numerous concepts outside the object paradigm; e.g. plans, communication, intentions, roles, and teams.

Designing Perception Modules to Shape Information for Agents

The difficulty associated with placing intelligent agents in environments is in part one of designing the means by which they sense their world. If the world is complex, or if the information available in the world is in an inappropriate form, then a mismatch between the information in the environment and the information required by the agent can exist. Practical means of dealing with this mismatch are available but designing the system requires careful modelling. By modelling perception as the module within the agent responsible for sensing and making sense of the environment several advantages are realised. The explicit representation of perception allows consideration of the issues, affords software engineering advantages with respect to the specification and design of systems and is compatible with many accepted definitions of agency.