handling, declarative goals, and planning

A BDI agent programming language with failur

Exploring the adaptive capacity of emergency management using agent based modelling

This project aimed to explore the suitability of Agent Based Modelling and Simulation (ABMS) technology in assisting planners and policy makers to better understand complex situations with multiple interacting aspects. The technology supports exploration of the impact of different factors on potential outcomes of a scenario, thus building understanding to inform decision making. To concretise this exploration a specific simulation tool was developed to explore response capacity around flash flooding in an inner Melbourne suburb, with a focus on sandbag depots as an option to be considered.The three types of activities delivered by this project to achieve its objectives were the development of an agent-based simulation, data collection to inform the development of the simulation and communication and engagement activities to progress the work. Climate change is an area full of uncertainties, and yet sectors such as Emergency Management and many others need to develop plans and policy responses regarding adaptation to these uncertain futures. Agent Based Modelling and Simulation is a technology which supports modelling of a complex situation from the bottom up, by modelling the behaviours of individual agents (often representing humans) in various scenarios. By running simulations with different configurations it is possible to explore and analyse a very broad range of potential options, providing a detailed understanding of potential risks and outcomes, given particular alternatives. This project explored the suitability of this technology for use in assessing and developing the capacity of the emergency response sector, as it adapts to climate change. A simulation system was developed to explore a particular issue regarding protection of property in a suburb prone to flash flooding. In particular the option of providing sandbag depots was explored. Simulations indicated that sandbag depots provided by CoPP or VicSES were at this time not a viable option. The simulation tool was deemed to be very useful for demonstrating this to community members as well as to decision makers. An interactive game was also developed to assist in raising awareness of community members about how to sandbag their property using on-site sandbags. The technology was deemed to be of great potential benefit to the sector and areas for further work inorder to realise this benefit were identified. In addition to developing awareness of useful technology, this project also demonstrated the critical importance of interdisciplinary team work, and close engagement with stakeholders and end users, if valuable technology uptake is to be realised. &nbsp

Using MATSim as a Component in Dynamic Agent-Based Micro-Simulations

This paper discusses use of the widely used transport simulator, MATSim, as one component in a large complex agent based microsimulation where dynamic changes in the environment require the agents to be reactive as well as goal directed. We describe a number of refinements to MATSim that have been made to facilitate its use within our deployed wildfire evacuation applications, as well as some tools that have been developed which complement MATSim. All code is freely available under open source licenses. As applications increasingly require complex microsimulations, with many aspects, it is important to use existing software where possible. However most simulation systems, like MATSim, have been developed as standalone systems. We identify ways that MATSim has needed to be extended or modified in order for it to be used as a component in a larger whole. The paper provides details that will be useful for anyone wanting to use MATSim within their specific application

An agent-oriented approach to change propagation in software evolution

Software maintenance and evolution are inevitable activities since almost all software that is useful and successful stimulates user-generated requests for change and improvements. One of the most critical problems in software maintenance and evolution is to maintain consistency between software artefacts by propagating changes correctly. Although many approaches have been proposed, automated change propagation is still a significant technical challenge in software engineering. In this paper we present a novel, agent-oriented approach to deal with change propagation in evolving software systems that are developed using the Prometheus methodology. A metamodel with a set of the Object Constraint Language (OCL) rules forms the basis of the proposed framework. The underlying change propagation mechanism of our framework is based on the well-known Belief-Desire-Intention (BDI) agent architecture. Traceability information and design heuristics are also incorporated into the framework to facilitate the change propagation process

HTN-Like Solutions for Classical Planning Problems: An Application to BDI Agent Systems

In this paper we explore the question of what characterises a desirable plan of action and how such a plan could be computed, in the context of systems that already possess a certain amount of hierarchical domain knowledge. In contrast to past work in this setting, which focuses on generating low-level plans, losing much of the domain knowledge inherent in such systems, we argue that plans ought to be HTN-like or abstract, i.e., re-use and respect the user-supplied know-how in the underlying domain. In doing so, we recognise an intrinsic tension between striving for abstract plans but ensuring that unnecessary actions, not linked to the specific goal to be achieved, are avoided. We explore this tension by characterising the set of “ideal” abstract plans that are non-redundant but maximally abstract, and then develop a more limited yet feasible account in which a given (arbitrary) abstract plan is “specialised” into one such non-redundant plan that is as abstract as possible. We present an algorithm that can compute such specialisations, and analyse the theoretical properties of our proposal

Integrating BDI agents with agent-based simulation platforms

This paper describes an integration framework that allows development of simulations where the cognitive reasoning and decision making is programmed and executed within an existing BDI (Belief, Desire, Intention) system, and the simulation is played out in an existing ABM (Agent Based Modelling) system. The framework has a generic layer which manages communication and synchronisation, a system layer which integrates specific BDI and ABM systems, and the application layer which contains the program code for a particular application. The code is available on GitHub: https://github.com/agentsoz/bdi-abm-integratio

Integrating BDI agents into a MATSim simulation

MATSim is a mature and powerful traffic simulator, used for large scale traffic simulations, primarily to assess likely results of various infrastructure or road network changes. More recently there has been work to extend MATSim to allow its use in applications requiring what has been referred to as "within day replanning". In the work described here we have coupled MATSim with a BDI (Belief Desire Intention) system to allow both more extensive modelling of the agent's decision making, as well as reactivity to environmental situations. The approach used allows for all agents to be "intelligent" or for some to be "intelligent"/reactive, while others operate according to plans that are static within a single day. The former is appropriate for simulations such as a bushfire evacuation, where all agents will be reacting to the changing environment. The latter is suited to introducing agents such as taxis into a standard MATSim simulation, as they cannot realistically have a predetermined plan, but must constantly respond to the current situation. We have prototype applications for both bushfire evacuation and taxis. By extending the capabilities of MATSim to allow agents to respond intelligently to changes in the environment, we facilitate the use of MATSim in a wide range of simulation applications. The work also opens the way for MATSim to be used alongside other simulation components, in a simulation integrating multiple components

Integrating BDI agents with Agent-based simulation platforms

Agent-Based Models (ABMs) is increasingly being used for exploring and supporting decision making about social science scenarios involving modelling of human agents. However existing agent-based simulation platforms (e.g., SWARM, Repast) provide limited support for the simulation of more complex cognitive agents required by such scenarios. We present a framework that allows Belief-Desire Intention (BDI) cognitive agents to be embedded in an ABM system. Architecturally, this means that the "brains" of an agent can be modelled in the BDI system in the usual way, while the "body" exists in the ABM system. The architecture is exible in that the ABM can still have non-BDI agents in the simulation, and the BDI-side can have agents that do not have a physical counterpart (such as an organisation). The framework addresses a key integration challenge of coupling event-based BDI systems, with time-stepped ABM systems. Our framework is modular and supports integration off-the-shelf BDI systems with off-the-shelf ABM systems. The framework is Open Source, and all integrations and applications are available for use by the modelling community