Abstract
Standards have had much importance in different fields of research in order to assure a certain quality of service in bilateral contracts. More specifically, in multi-agent systems performance standards may be used in order to articulate contracts among partners in environments dealing with uncertainty. However, little effort has been made on how to ensure standards compliance over time. In this work we put forward a learning-based mechanism that attempts to maintain performance standards by applying incentives and/or punishments to agents identified as specialised for certain tasks. We present some empirical results supporting our approach.
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Hermoso, R., Cardoso, H.L. (2013). Dynamically Maintaining Standards Using Incentives. In: Pérez, J., et al. Trends in Practical Applications of Agents and Multiagent Systems. Advances in Intelligent Systems and Computing, vol 221. Springer, Cham. https://doi.org/10.1007/978-3-319-00563-8_11
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DOI: https://doi.org/10.1007/978-3-319-00563-8_11
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-00562-1
Online ISBN: 978-3-319-00563-8
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