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Learning Systems Engineering

Learning Systems Engineering

Valentina Plekhanova
Copyright: © 2008 |Pages: 10
ISBN13: 9781599049359|ISBN10: 159904935X|EISBN13: 9781599049366
DOI: 10.4018/978-1-59904-935-9.ch114
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MLA

Plekhanova, Valentina. "Learning Systems Engineering." Online and Distance Learning: Concepts, Methodologies, Tools, and Applications, edited by Lawrence A. Tomei, IGI Global, 2008, pp. 1429-1438. https://doi.org/10.4018/978-1-59904-935-9.ch114

APA

Plekhanova, V. (2008). Learning Systems Engineering. In L. Tomei (Ed.), Online and Distance Learning: Concepts, Methodologies, Tools, and Applications (pp. 1429-1438). IGI Global. https://doi.org/10.4018/978-1-59904-935-9.ch114

Chicago

Plekhanova, Valentina. "Learning Systems Engineering." In Online and Distance Learning: Concepts, Methodologies, Tools, and Applications, edited by Lawrence A. Tomei, 1429-1438. Hershey, PA: IGI Global, 2008. https://doi.org/10.4018/978-1-59904-935-9.ch114

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Abstract

Traditionally multi-agent learning is considered as the intersection of two subfields of artificial intelligence: multi-agent systems and machine learning. Conventional machine learning involves a single agent that is trying to maximise some utility function without any awareness of existence of other agents in the environment (Mitchell, 1997). Meanwhile, multi-agent systems consider mechanisms for the interaction of autonomous agents. Learning system is defined as a system where an agent learns to interact with other agents (e.g., Clouse, 1996; Crites & Barto, 1998; Parsons, Wooldridge & Amgoud, 2003). There are two problems that agents need to overcome in order to interact with each other to reach their individual or shared goals: since agents can be available/unavailable (i.e., they might appear and/or disappear at any time), they must be able to find each other, and they must be able to interact (Jennings, Sycara & Wooldridge, 1998).

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