In this paper we present a new agent-based model, CDYS – Complex DYnamic System, for intelligent, flexible, and context-aware multi-modal interaction on autonomous system. This model is focused on context models which facilitate the communication and the knowledge representation with an highly-customized and adaptable representation and distribution of the entities composing the environment. CDYS uses information from multiple perceptions and provides proactive real-time updates and context-specific guidance in the state representation and synthesis. Our work includes the design of interaction, evolution, context definition by states and ontologies; communication, context, task models based on these ontologies, a set of representations of perception to drive agent behavior, communication, and a compatible integration of rules and machine learning aimed to improve information retrieval and the Semantic web. Currently, we have completed the first stage of our research, producing first pass Ontologies, models, and the interaction to apply genetic algorithm to improve the global ontology, by local ontology representation, tested with an initial prototype of a small-scale test-bed on clustering for self improving of the agent’s knowledge base .Our approach is based on social systems in context-aware applications, informed by Autopoietic Systems, to use a system (an agent) that is able to describe and manage the evolution of its environment and of the knowledge base in the autopoietic based model.