Revise for Decision Mathematics 1

Revise for Decision Mathematics 1
Title Revise for Decision Mathematics 1 PDF eBook
Author John Hebborn
Publisher Heinemann
Pages 76
Release 2001
Genre Juvenile Nonfiction
ISBN 9780435511197

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Revision book written specifically for the Edexcel AS and A Level exams offering: worked examination questions and examples with hints on answering examination questions successfully; test-yourself section; key points reinforcing what students have learned; and answers to all questions.

Decision Mathematics

Decision Mathematics
Title Decision Mathematics PDF eBook
Author
Publisher
Pages 464
Release 1990
Genre Decision making
ISBN

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A-Level Mathematics for AQA Decision Maths 1

A-Level Mathematics for AQA Decision Maths 1
Title A-Level Mathematics for AQA Decision Maths 1 PDF eBook
Author Richard Parsons
Publisher Coordination Group Publication
Pages 194
Release 2012-07-01
Genre A-level examinations
ISBN 9781847627971

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AS/A Level Maths for AQA - Decision Maths 1: Student Book

Decision Mathematics

Decision Mathematics
Title Decision Mathematics PDF eBook
Author John Hebborn
Publisher Heinemann
Pages 296
Release 2000
Genre Mathematics
ISBN 9780435510800

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A syllabus-specific textbook providing worked examples, exam-level questions and many practice exercises, in accordance to the new Edexcel AS and Advanced GCE specification.

Revise for Pure Mathematics 1

Revise for Pure Mathematics 1
Title Revise for Pure Mathematics 1 PDF eBook
Author Michael Kenwood
Publisher Heinemann
Pages 68
Release 2001
Genre Juvenile Nonfiction
ISBN 9780435511104

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Revision book written specifically for the Edexcel AS and A Level exams offering: worked examination questions and examples with hints on answering examination questions successfully; test-yourself section; key points reinforcing what students have learned; and answers to all questions.

Revise for Core Mathematics C1

Revise for Core Mathematics C1
Title Revise for Core Mathematics C1 PDF eBook
Author Pledger
Publisher Heinemann
Pages 88
Release 2005
Genre Mathematics
ISBN 9780435511227

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The clear route to A Level success - new Core titles for the new specification Written by the same authors as the textbooks for a complete match, so are ideal for use alongside the course books. Worked examination questions and examples with hints on answering questions successfully help students push for those top grades. A test-yourself section makes sure students are fully prepared for the exam. Key points help reinforce learning and help students reach their best potential. Answers to all the questions ensure students can check their work. Written by experienced Senior Examiners.

Algorithms for Decision Making

Algorithms for Decision Making
Title Algorithms for Decision Making PDF eBook
Author Mykel J. Kochenderfer
Publisher MIT Press
Pages 701
Release 2022-08-16
Genre Computers
ISBN 0262047012

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A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them. Automated decision-making systems or decision-support systems—used in applications that range from aircraft collision avoidance to breast cancer screening—must be designed to account for various sources of uncertainty while carefully balancing multiple objectives. This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them. The book first addresses the problem of reasoning about uncertainty and objectives in simple decisions at a single point in time, and then turns to sequential decision problems in stochastic environments where the outcomes of our actions are uncertain. It goes on to address model uncertainty, when we do not start with a known model and must learn how to act through interaction with the environment; state uncertainty, in which we do not know the current state of the environment due to imperfect perceptual information; and decision contexts involving multiple agents. The book focuses primarily on planning and reinforcement learning, although some of the techniques presented draw on elements of supervised learning and optimization. Algorithms are implemented in the Julia programming language. Figures, examples, and exercises convey the intuition behind the various approaches presented.