Pilots of the future: human or computer?
Communications of the ACM - Special issue: computing in the frontiers of science and engineering
Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Artificial fishes: physics, locomotion, perception, behavior
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
Agent theories, architectures, and languages: a survey
ECAI-94 Proceedings of the workshop on agent theories, architectures, and languages on Intelligent agents
Applications of intelligent agents
Agent technology
Understanding agent systems
Machines Who Think
Introduction to Multiagent Systems
Introduction to Multiagent Systems
Autonomous Agents and Multi-Agent Systems
Is it an Agent, or Just a Program?: A Taxonomy for Autonomous Agents
ECAI '96 Proceedings of the Workshop on Intelligent Agents III, Agent Theories, Architectures, and Languages
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Research Directions in the KES Centre
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
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Heuristic computing has consolidated into two streams of research (personification software and smart products) [1]. Cognitive Science is one of these fields and is attracting research effort based on Multi-Agent System (MAS). This research requires the formation of a voluntarily trust relationship in order for collaboration to occur, otherwise the imposed goal(s) may be aborted or fail completely [2,3]. An Agent Transportation Layer Adaption System (ATLAS) communications framework has been constructed to pass messages between separate agent systems. Discussion about confined frameworks have recently been extended to enable individual students associated with our Knowledge-Based and Intellingent Information and Engineering Systems (KES) Centre to fast track the development of their research concepts. A Plug 'n' Play concept based on a multi-agent blackboard architecture forms the basis of this research. This paper highlights the core architecture, we believe is required for Multi-Agent System (MAS) developers to achieve such flexibility. Agent teams can provide the ability to adapt and dynamically organize. The model described, concentrates on the blackboard design constructs to represents all functional blocks required to automate the processes required to complete any decomposed goals. Discussion in this paper is limited to the formative work within the foundation layers of that framework.