AgentSpeak(L): BDI agents speak out in a logical computable language
MAAMAW '96 Proceedings of the 7th European workshop on Modelling autonomous agents in a multi-agent world : agents breaking away: agents breaking away
Computer
Agents in object-oriented software engineering
Software—Practice & Experience - Research Articles
ICMB '05 Proceedings of the International Conference on Mobile Business
CMP: A UML Context Modeling Profile for Mobile Distributed Systems
HICSS '07 Proceedings of the 40th Annual Hawaii International Conference on System Sciences
A platform-independent metamodel for multiagent systems
Autonomous Agents and Multi-Agent Systems
Context-aware systems: A literature review and classification
Expert Systems with Applications: An International Journal
Malaca: A component and aspect-oriented agent architecture
Information and Software Technology
Review: Ambient intelligence: Technologies, applications, and opportunities
Pervasive and Mobile Computing
Support for aspectual modeling to Multiagent system architecture
EA '09 Proceedings of the 2009 ICSE Workshop on Aspect-Oriented Requirements Engineering and Architecture Design
FAML: A Generic Metamodel for MAS Development
IEEE Transactions on Software Engineering
Agent factory micro edition: a framework for ambient applications
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part III
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Ambient Intelligence (AmI) systems are inherently context aware, since they should be able to react to, adapt to and even anticipate user actions or events occurring in the environment in a manner consistent with the current context. Software agents and especially the BDI architecture are considered to be a promising approach to deal with AmI systems development. However current agent models do not offer a proper support for developing AmI systems because they do not offer support to model explicitly the interaction between the agent, context sources and effectors, and the context-awareness features are scattered in the system model. To solve these problems we propose an aspectoriented agent metamodel for AmI systems, which encourages modularity in the description of context-aware features in AmI systems. This metamodel achieves better results than other metamodels in separation of concerns, size, coupling and cohesion.