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Наименование:

Ensemble Case Based Learning for Multi-Agent Systems

Автор:
мягкая обложка
300 страниц
2008 год
Издательство:   Книга по Требованию
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Описание:This book presents a framework for machine learning in a distributed data scenario with decentralized decision making. Moreover, we are interested in autonomous agents that collaboratively work as ensembles. Each individual agent in a MAC system is capable of individually learn and solve problems using CBR with an individual case base. We have based our framework in Multi-Agent Systems (MAS), and in Case-Based Reasoning (CBR). Moreover, each case base is owned and managed by an individual agent, and any information is disclosed or shared only if the agent decides so. Thus, this framework preserves the privacy of data, and the autonomy to disclose data. The focus of this book is to develop strategies so that individual learning agents improve their performance both individually and as an ensemble. The techniques presented fall in between the fields of CBR and MAS, and thus they aim at providing insights on how to successfully combine both fields. Specifically, we present the Multi-Agent Case Based Reasoning (MAC) framework, a multi-agent approach to CBR.


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Essays

If you describe your web-based database as "a system to allow people to collaboratively leverage the value of information," it will go in one investor ear and out the other. They'll just discard that sentence as meaningless boilerplate, and hope, with increasing impatience, that in the next sentence you'll actually explain what you've made. Your primary goal is not to describe everything your system might one day become, but simply to convince investors you're worth talking to further. So approach this like an algorithm that gets the right answer by successive approximations. Begin with a description that's gripping but perhaps overly narrow, then flesh it out to the extent you can. It's the same principle as incremental development: start with a simple prototype, then add features, but at every point have working code. In this case, "working code" means a working description in the investor's head. 4. Don't talk and drive. Have one person talk while another uses the computer. If the same person does both, they'll inevitably mumble downwards at the computer screen instead of talking clearly at the audience ...»

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