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The service interaction agent would drive more effective service compositions with enhanced operation reasoning applications.
The EHS comprises intelligent agents: interaction agent, instruction agent, information agent, evaluation agent and log agent.
In future work, we plan to extend the approach by introducing service recommendation engine and service interaction agent.
Starting from a cognitive architecture for Natural Interaction, an agent-based design is presented, focusing particularly on the role of the interaction agent.
The prototype consists of a micro mobile robot as a physical interaction agent, a camera and a microphone and a computer.
We investigated the influence of separation conditions, namely mobile phase composition (ion interaction agent content, pH and organic constituent content), on sequence-dependent separation by means of ion-interaction RPLC (II-RPLC) using two types of models: experimental design artificial neural networks (ED-ANN), and linear regression based on molecular dynamics data.
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With each interaction, agents exchange opinions and the consensus strength increases, but with different growth rates for different configurations of (gamma) and (beta).
In an interaction, agents compare their self-appreciation to the appreciation of their peers towards themselves, and as a consequence of this comparison, change both their self-appreciation and peer-appreciation of other agents.
Coordination level includes the basic protection functions and others based on information interaction: searching agent, fault detection agent, fault line selection agent.
Through such interactions, agents alter their states until some criteria are met or the system reaches an equilibrium state.
Our model introduces a spatial restriction in the structure of interactions: agents are embedded on a regular lattice and they can only bargain with their spatial neighbours.
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