1,676 research outputs found
Simulation of complex environments:the Fuzzy Cognitive Agent
The world is becoming increasingly competitive by the action of liberalised national and global markets. In parallel these markets have become increasingly complex making it difficult for participants to optimise their trading actions. In response, many differing computer simulation techniques have been investigated to develop either a deeper understanding of these evolving markets or to create effective system support tools. In this paper we report our efforts to develop a novel simulation platform using fuzzy cognitive agents (FCA). Our approach encapsulates fuzzy cognitive maps (FCM) generated on the Matlab Simulink platform within commercially available agent software. We firstly present our implementation of Matlab Simulink FCMs and then show how such FCMs can be integrated within a conceptual FCA architecture. Finally we report on our efforts to realise an FCA by the integration of a Matlab Simulink based FCM with the Jack Intelligent Agent Toolkit
Exploring Knowledge Engineering Strategies in Designing and Modelling a Road Traffic Accident Management Domain
Formulating knowledge for use in AI Planning engines
is currently something of an ad-hoc process,
where the skills of knowledge engineers and the
tools they use may significantly influence the quality
of the resulting planning application. There is
little in the way of guidelines or standard procedures,
however, for knowledge engineers to use
when formulating knowledge into planning domain
languages such as PDDL. This paper seeks to investigate
this process using as a case study a road
traffic accident management domain.
Managing road accidents requires systematic,
sound planning and coordination of resources to
improve outcomes for accident victims. We have
derived a set of requirements in consultation with
stakeholders for the resource coordination part
of managing accidents. We evaluate two separate
knowledge engineering strategies for encoding the
resulting planning domain from the set of requirements:
(a) the traditional method of PDDL experts
and text editor, and (b) a leading planning GUI with
built in UML modelling tools.
These strategies are evaluated using process and
product metrics, where the domain model (the
product) was tested extensively with a range of
planning engines. The results give insights into the
strengths and weaknesses of the approaches, highlight
lessons learned regarding knowledge encoding,
and point to important lines of research for
knowledge engineering for planning
Model based testing for agent systems
Although agent technology is gaining world wide popularity, a hindrance to its uptake is the lack of proper testing mechanisms for agent based systems. While many traditional software testing methods can be generalized to agent systems, there are many aspects that are different and which require an understanding of the underlying agent paradigm. In this paper we present certain aspects of a testing framework that we have developed for agent based systems. The testing framework is a model based approach using the design models of the Prometheus agent development methodology. In this paper we focus on unit testing and identify the appropriate units, present mechanisms for generating suitable test cases and for determining the order in which the units are to be tested, present a brief overview of the unit testing process and an example. Although we use the design artefacts from Prometheus the approach is suitable for any plan and event based agent system
Automated unit testing intelligent agents in PDT
The Prometheus Design Tool (PDT) is an agent development tool that supports the Prometheus design methodology and includes features like automated code generation. We enhance this tool by adding a feature that allows the automated unit testing of agents that are built from within PDT
Prioritisation mechanisms to support incremental development of agent systems
It is often necessary to partition a project into different priority levels and to develop incrementally. This paper presents a mechanism whereby a developer can prioritise scenarios on a five point scale, leading to automated, coherent partitioning of all required design entities, according to the three IEEE defined priority levels of essential, conditional and optional, which are used in many companies. This allows for automated support to guide the developer as to what design artefacts need to be developed at each phase. The developer can indicate the relative sizes desired for the three partitions and the algorithm described will attempt to get as close to this as possible. It is also possible to move items manually to achieve better sized partitions, as long as priority orderings are not violated. The approach is fast and easy to apply at various times during development, as needed
- …