Wardell Dean (16 results)

Condition: Very Good. Most items will be dispatched the same or the next working day. A copy that has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Condition: New.

Paperback or Softback. Condition: New. Application of Fuzzy State Aggregation and Policy Hill Climbing to Multi-Agent Systems in Stochastic Environments. Book.

Condition: As New. Unread book in perfect condition.

Condition: New. In English.

Condition: New.

Condition: As New. Unread book in perfect condition.

Taschenbuch. Condition: Neu. Neuware - Reinforcement learning is one of the more attractive machine learning technologies, due to its unsupervised learning structure and ability to continually learn even as the operating environment changes. Applying this learning to multiple cooperative software agents (a multi-agent system) not only allows each individual agent to learn from its own experience, but also opens up the opportunity for the individual agents to learn from the other agents in the system, thus accelerating the rate of learning. This research presents the novel use of fuzzy state aggregation, as the means of function approximation, combined with the fastest policy hill climbing methods of Win or Lose Fast (WoLF) and policy-dynamics based WoLF (PD-WoLF). The combination of fast policy hill climbing and fuzzy state aggregation function approximation is tested in two stochastic environments; Tileworld and the simulated robot soccer domain, RoboCup. The Tileworld results demonstrate that a single agent using the combination of FSA and PHC learns quicker and performs better than combined fuzzy state aggregation and Q-learning reinforcement learning alone. Results from the multi-agent RoboCup domain again illustrate that the policy hill climbing algorithms perform better than Q-learning alone in a multi-agent environment. The learning is further enhanced by allowing the agents to share their experience through a weighted strategy sharing.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.…

Condition: New. KlappentextrnrnReinforcement learning is one of the more attractive machine learning technologies, due to its unsupervised learning structure and ability to continually learn even as the operating environment changes. Applying this learning to m.

Soft Cover. Condition: Very Good. First Edition. 64 pages. 30 grams. This book is in very good unmarked condition. 'Any woman who has had to wait for a simple repair job to be done, will welcome the independence provided by the information in this book. Methods for safely carrying out basic repairs are clearly set out, but the woman is advised when she should summon an expert. The handywoman will be able to - Repair a fuse; Fix simple problems in electrical appliances; Correct malfunctions at plumbing; Keep out damp and draughts; Rid the house of pests; Remove stains in the house and yard; Cope with painting, finishing, and sealing; keep the lawnmower in working order; Perform many other basic repairs and generally maintain her house efficiently.' 24mo - over 5" - 5¾" tall. Quantity Available: 1. Category: Non-fiction, Reference.; ISBN: 0851799299. ISBN/EAN: 9780851799292. Pictures of this item not already displayed here available upon request. Inventory No: 000407.…

PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condition: New. Print on Demand pp. 82.

Condition: New. Print on Demand pp. 82.

Condition: New. PRINT ON DEMAND pp. 82.

Paperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.