Abstract
A multiagent system [76] can be defined as a group of autonomous, interacting entities sharing a common environment, which they perceive with sensors and upon which they act with actuators. Multiagent systems are finding applications in a wide variety of domains including robotic teams [65], distributed control [69], data mining [73] and resource allocation [25]. They may arise as the most natural way of looking at the system, or may provide an alternative perspective on systems that are originally regarded as centralized. For instance, in robotic teams the control authority is naturally distributed among the robots [65]. In resource management, while resources can be managed by a central authority, identifying each resource with an agent may provide a helpful, distributed perspective on the system [25].
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© 2014 Springer International Publishing Switzerland
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Chakraborty, D. (2014). Introduction. In: Sample Efficient Multiagent Learning in the Presence of Markovian Agents. Studies in Computational Intelligence, vol 523. Springer, Cham. https://doi.org/10.1007/978-3-319-02606-0_1
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DOI: https://doi.org/10.1007/978-3-319-02606-0_1
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02605-3
Online ISBN: 978-3-319-02606-0
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