Rebel (ROADMAP) - toolkit for agent-oriented sofware development
The Agentlab has developed a new approach, known as the ROADMAP methodology that incorporates new role models and has the ability for customising features and for incorporating other methodologies. The Agentlab is funded to develop agent methodologies and prototype tools that support rapid implementation of multi-agent software.
MIT Press will release a book in 2009, entitled The Art of Agent-Oriented Modelling, by Agentlab members Leon Sterling and Kuldar Taveter.
The book, the ROADMAP technique along with the Rebel toolkit and the MindiGolog agent programming language is used in teaching the subject
Software Agents (Agent programming languages).
Leon Sterling and Kuldar Taveter. The Art of Agent-Oriented Modelling. MIT Press, 2009.
Rebel is a tool for the ROADMAP methodology.
REBEL RCP Version 1.1.0, a rich client stand-alone application:
Download for Mac OS X (12.4MB)
Download for Windows (12.9MB)
REBEL Version 1.0.0, a plug-in for Eclipse: RebelInstallation.zip (5.5MB)
MIndiGolog - Logic programming and planning language for multi-agent systems
MIndiGolog is a multi-agent variant of the well-known, high-level agent programming language IndiGolog, based on the situation calculus.
MIndiGolog was written by Ryan Kelly, as part of the Agent Programming Languages project conducted by Adrian Pearce.
Students use MIndiGolg in the Masters/Honours subject
Software Agents (Agent programming languages) for coding solutions.
This MIndiGolog implementation
performs online execution planning
but is limited to synchronous domains. This software runs on the Mozart
platform version 1.3.2 or later. Its key feature is the use of Mozart's
parallel search functionality to distribute the execution planning
This MIndiGolog implementation
produces joint executions as
the output of its planning process, and is limited to only offline
planning. It is able to render a graphical representation of joint
executions in the Graphviz DOT language, from which the diagrams
are generated. This version also runs
on the Mozart platform version 1.3.2 or later.
This is our preliminary implementation of an epistemic
It is implemented using SWI-Prolog to perform
symbolic manipulation, calling a modified version of the PDL prover
from the Tableaux Workbench suite to handle
the resulting modal logic queries.
CollabLP - Logic programming language for multi-agent systems
Collaborative logic programming is based on a new deductive-inductive resolution technique, by combining
deductive theorem proving with inductive logic programming, for solving a new class of multiagent
problems - namely collaborative logic programming (CollabLP) problems.
CollabLP was written by
Jian (Alan) Huang and is available for experimentation upon request.
NICTA Open Sensor-web Architecture (NOSA) - standards complient middleware for sensor-networks
The NICTA Open SensorWeb Architecture (NOSA) project has develped a complete standards compliant platform and middleware for integration of sensor networks for emerging distributed computing platforms.
NOSA is a built upon the Sensor Web Enablement (SWE) standard defined by the Open GIS Consortium (OGC), which is composed of a set of specifications, including SensorML, Observation & Measurement, Sensor Collection Service, Sensor Planning Service and Web Notification Service.
It presents a reusable, scalable, extensible, and interoperable service oriented Sensor Web architecture that (i) conforms to the SWE standard; (ii) integrates Sensor Web with Grid Computing and (iii) provides middleware support for Sensor Webs.
For more information, please visit the NICTA's NOSA website here.
Human-agent virtual environment (HAVE) & Capture the flag (CTF) - multi-agent simulations
HAVE & CTF are human-agent virtual environment and capture-the-flag multi-agent simulations. The simulations were written by
Michael Papasimeon, please contact Michael, who works at
DSTO, if you are interested in this software.
Publications on multi-agent simulation (and HAVE)