The next generation of air traffic control will require automation in order to meet safety, reliability, flexibility, and robustness demands in an environment of steadily increasing air traffic density. Optimization, however, is an inadequate paradigm for the design of a cooperative distributed air traffic control system. The problem stems from a fundamental limitation of von Neumann-Morgenstern utilities, which do not account for sophisticated social behavior such as situational altruism. Social utility functions overcome this limitation by permitting decision makers to expand their spheres of interest beyond the self via conditional utilities. Satisficing game theory provides a decision strategy that permits decision makers to compromise in the interest of achieving both individual and group goals and presents a mathematical framework for the design of sophisticated cooperative multiagent societies. Simulation results in a variety of geometric scenarios show promising performance in terms of efficiency and flexibility even with high traffic densities.
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