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One of the key issues in human-automated system interaction scenarios is deciding what decisions and tasks are best done with humans, or automated systems, or a combination of each. In general, these two entities possess complimentary skill sets. Humans perform extremely well dealing with unforeseen events or new tasks. On the other hand, autonomous systems excel in performing routine work tasks, and in well-defined problem areas. In the area of human-system interaction, our research focuses on using basic scientific and engineering methodologies necessary for improving human-agent system performance that results in a synergistic method for decision-making and task coordination in real-world scenarios.
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