Abstract
This chapter presents a view of agent autonomy based on decision-making control. Theoretical and empirical research results are presented supporting the performance improvements that can be leveraged by implementing adaptive autonomy through the capability of Adaptive Decision-Making Frameworks (ADMF). This analysis shows, in theory, that ADMF should outperform static or random decision-making frameworks as agents operate in a multi-agent system. ADMF is also shown, through empirically defined performance measures, to be more robust and to perform better over time than other types of decision-making framework policies. ADMF is therefore a form of adaptive agent autonomy with very great potential power.
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Barber, K.S., Gamba, I.M., Martin, C.E. (2003). Representing and Analyzing Adaptive Decision-Making Frameworks. In: Hexmoor, H., Castelfranchi, C., Falcone, R. (eds) Agent Autonomy. Multiagent Systems, Artificial Societies, and Simulated Organizations, vol 7. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-9198-0_3
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DOI: https://doi.org/10.1007/978-1-4419-9198-0_3
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