Abstract
Broadly, distributed problem solving is a subfield within multiagent systems, where the focus is to enable multiple agents to work together to solve a problem. These agents are often assumed to be cooperative, that is, they are part of a team or they are self-interested but incentives or disincentives have been applied such that the individual agent rewards are aligned with the team reward. We illustrate the motivations for distributed problem solving with an example. Imagine a decentralized channel-allocation problem in a wireless local area network (WLAN), where each access point (agent) in the WLAN needs to allocate itself a channel to broadcast such that no two access points with overlapping broadcast regions (neighboring agents) are allocated the same channel to avoid interference. Figure 1 shows example mobile WLAN access points, where each access point is a Create robot fitted with a wireless CenGen radio card. Figure 2a shows an illustration of such a problem with three access points in a WLAN, where each oval ring represents the broadcast region of an access point. Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.
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CITATION STYLE
Yeoh, W., & Yokoo, M. (2012). Distributed problem solving. In AI Magazine (Vol. 33, pp. 53–65). AI Access Foundation. https://doi.org/10.1609/aimag.v33i3.2429
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