Abstract
Multimedia communication in mobile and ad hoc networks used by real time applications can be improved by adding intelligent and adaptive cababilities. This new functionality will allow them to adapt to contantly and unpredictably changing network conditions. Derived from this adaptivity, the user will perceive a more or less constant quality instead of the high variable quality perceived in nowadays applications. In this work, we maintain the following thesis: both machine learning and intelligent agents will play an important role in the improvement of the aplications we mentioned above. Machine learning, by means of reinforcement learning will provide adaptivity. Intelligent agents will ease P2P computation. This paper focuses on approaches for both topics.
Work supported by the FIT-070000-2003-662, FIT-1603002003-41 and TIC2002-04021-C02-01 projects).
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Botía, J.A., Ruiz, P., Sánchez, J.A., Gómez Skarmeta, A.F. (2004). Adaptive P2P Multimedia Communication Using Hybrid Learning. In: Conejo, R., Urretavizcaya, M., Pérez-de-la-Cruz, JL. (eds) Current Topics in Artificial Intelligence. TTIA 2003. Lecture Notes in Computer Science(), vol 3040. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25945-9_12
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DOI: https://doi.org/10.1007/978-3-540-25945-9_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22218-7
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