A collective view and methodologies for software agents' interaction

Software agents' interactions are of special importance when a group of agents interact with each other to solve a problem that is beyond the capability and knowledge of each individual. Efficiency, performance and the overall quality of multi-agent applications depend mainly on how the agents interact with each other. We present an agent model by which we can distinguish different agent's interaction scenarios. The model has five attributes: goal; control; interface; identity; knowledge base. Using the model, we analyze and describe possible scenarios. Then, for each scenario, appropriate reasoning and decision-making techniques are devised. The model can readily be used in the design and implementation of multi-agent systems.