The objective of the proposed project is the development of technology for more efficient and effective human-computer supervision of complex systems. Systems that combine humans and automation in a synergistic or cooperative manner may be termed hybrid systems. Hybrid systems offer advantages over both purely automated systems and purely manual systems in many circumstances. However, future hybrid systems will be even more complex than contemporary ones. This gives rise to a serious need to develop methods for integrating humans more closely?and more efficiently?than is possible now within hybrid systems. We propose to apply a recent Raven Research innovation, Achievability Control Theory (ACT) to the problem of integrating multi-agent autonomous and semi-autonomous systems into human-machine teams. ACT is a superset of Supervisory Control Theory (SCT) which more synergistically combines human and machine capabilities and enhances the flexibility and effectiveness of hybrid robotic and automated systems. This approach allows for integration of multiple agents in a system and at same time promotes human-centric understanding and design of such a system.