7 Days With Dynamic Programming

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7 Days With Dynamic Programming

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Author : Aditya Chatterjee
language : en
Publisher: OpenGenus
Release Date : 2020-08-24

7 Days With Dynamic Programming written by Aditya Chatterjee and has been published by OpenGenus this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-24 with Computers categories.

Become Dynamic Programming Master in 7 days Do share your review with us. It will help us help you better. 👌 Dynamic Programming is one of the most important algorithmic domains and is equally challenging. With practice and correct way of thinking, you can master it easily. If a problem takes O(2^N) time to search a solution among possible solutions, Dynamic Programming has the potential to reduce it to O(N) or polynomial time thereby reducing the search space. We will attempt one problem every day in this week and analyze the problem deeply. Our schedule: • Day 1: Introduction + Longest Increasing Subsequence • Day 2: 2D version of Day 1 problems • Day 3: Dynamic Programming on Strings • Day 4: Modified version of Day 3 problems • Day 5: Dynamic Programming for String patterns (Longest Palindromic Substring) • Day 6: Modified version of Day 4 problems • Day 7: 2 conditions on 1 data point On following this routine sincerely, you will get a strong hold on Dynamic Programming and will be able to attempt interview and real-life problems easily. #7daysOfAlgo: a 7-day investment to Algorithmic mastery.

Dynamic Programming

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Author : Art Lew
language : en
Publisher: Springer
Release Date : 2006-10-05

Dynamic Programming written by Art Lew and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-10-05 with Computers categories.

This book provides a practical introduction to computationally solving discrete optimization problems using dynamic programming. From the examples presented, readers should more easily be able to formulate dynamic programming solutions to their own problems of interest. We also provide and describe the design, implementation, and use of a software tool that has been used to numerically solve all of the problems presented earlier in the book.

Dynamic Programming

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Author : Richard Bellman
language : en
Publisher: Courier Corporation
Release Date : 2013-04-09

Dynamic Programming written by Richard Bellman and has been published by Courier Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-09 with Mathematics categories.

Introduction to mathematical theory of multistage decision processes takes a "functional equation" approach. Topics include existence and uniqueness theorems, optimal inventory equation, bottleneck problems, multistage games, Markovian decision processes, and more. 1957 edition.

Approximate Dynamic Programming

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Author : Warren B. Powell
language : en
Publisher: John Wiley & Sons
Release Date : 2007-10-05

Approximate Dynamic Programming written by Warren B. Powell and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-10-05 with Mathematics categories.

A complete and accessible introduction to the real-world applications of approximate dynamic programming With the growing levels of sophistication in modern-day operations, it is vital for practitioners to understand how to approach, model, and solve complex industrial problems. Approximate Dynamic Programming is a result of the author's decades of experience working in large industrial settings to develop practical and high-quality solutions to problems that involve making decisions in the presence of uncertainty. This groundbreaking book uniquely integrates four distinct disciplines—Markov design processes, mathematical programming, simulation, and statistics—to demonstrate how to successfully model and solve a wide range of real-life problems using the techniques of approximate dynamic programming (ADP). The reader is introduced to the three curses of dimensionality that impact complex problems and is also shown how the post-decision state variable allows for the use of classical algorithmic strategies from operations research to treat complex stochastic optimization problems. Designed as an introduction and assuming no prior training in dynamic programming of any form, Approximate Dynamic Programming contains dozens of algorithms that are intended to serve as a starting point in the design of practical solutions for real problems. The book provides detailed coverage of implementation challenges including: modeling complex sequential decision processes under uncertainty, identifying robust policies, designing and estimating value function approximations, choosing effective stepsize rules, and resolving convergence issues. With a focus on modeling and algorithms in conjunction with the language of mainstream operations research, artificial intelligence, and control theory, Approximate Dynamic Programming: Models complex, high-dimensional problems in a natural and practical way, which draws on years of industrial projects Introduces and emphasizes the power of estimating a value function around the post-decision state, allowing solution algorithms to be broken down into three fundamental steps: classical simulation, classical optimization, and classical statistics Presents a thorough discussion of recursive estimation, including fundamental theory and a number of issues that arise in the development of practical algorithms Offers a variety of methods for approximating dynamic programs that have appeared in previous literature, but that have never been presented in the coherent format of a book Motivated by examples from modern-day operations research, Approximate Dynamic Programming is an accessible introduction to dynamic modeling and is also a valuable guide for the development of high-quality solutions to problems that exist in operations research and engineering. The clear and precise presentation of the material makes this an appropriate text for advanced undergraduate and beginning graduate courses, while also serving as a reference for researchers and practitioners. A companion Web site is available for readers, which includes additional exercises, solutions to exercises, and data sets to reinforce the book's main concepts.

Dynamic Programming

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Author : Eric V. Denardo
language : en
Publisher: Courier Corporation
Release Date : 2012-12-27

Dynamic Programming written by Eric V. Denardo and has been published by Courier Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-27 with Mathematics categories.

Designed both for those who seek an acquaintance with dynamic programming and for those wishing to become experts, this text is accessible to anyone who's taken a course in operations research. It starts with a basic introduction to sequential decision processes and proceeds to the use of dynamic programming in studying models of resource allocation. Subsequent topics include methods for approximating solutions of control problems in continuous time, production control, decision-making in the face of an uncertain future, and inventory control models. The final chapter introduces sequential decision processes that lack fixed planning horizons, and the supplementary chapters treat data structures and the basic properties of convex functions. 1982 edition. Preface to the Dover Edition.

Dynamic Programming For The Day Before Your Coding Interview

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Author : Ue Kiao
language : en
Publisher:
Release Date : 2020-04-28

Dynamic Programming For The Day Before Your Coding Interview written by Ue Kiao and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-28 with categories.

Dynamic Programming is a fundamental algorithmic technique which is behind solving some of the toughest computing problems.In this book, we have covered some Dynamic Programming problems which will give you the general idea of formulating a Dynamic Programming solution and some practice on applying it on a variety of problems.Some of the problems we have covered are: * Permutation coefficientThis is a basic problem but is significant in understanding the idea behind Dynamic Programming. We have used this problem to: * Present the two core ideas of Dynamic Programming to make the idea clear and help you understand what Dynamic Programming mean. * Show another approach which can same performance (in terms of time complexity) and understand how it is different from our Dynamic Programming approach* Longest Common SubstringThis is an important problem as we see how we can apply Dynamic Programming in string problems. In the process, we have demonstrated the core ideas of handling string data which helps in identifying the cases when Dynamic Programming is the most efficient approach.* XOR valueThis is another significant problem as we are applying Dynamic Programming on a Number Theory problem more specifically problem involving subset generation. The search space is exponential in size but with our efficient approach, we can search the entire data in polynomial time which is a significant improvement.This brings up a fundamental power of Dynamic Programming: Search exponential search space in polynomial time* K edgesIn line with our previous problems, in this problem, we have applied Dynamic Programming in a graph-based problem. This is a core problem as in this we learn that: * Dynamic Programming makes the solution super-efficient * Extending the Dynamic Programming solution using Divide and Conquer enables us to solve it more efficientlyThis problem shows a problem where Dynamic Programming is not the most efficient solution but is in the right path.We have covered other relevant solutions and ideas as well so that you have the complete idea of the problems and understand deeply the significance of Dynamic Programming in respect to the problems.This book has been carefully prepared and reviewed by Top programmers and Algorithmic researchers and members of OpenGenus. We would like to thank Aditya Chatterjee and Ue Kiao for their expertise in this domain and reviews from professors at The University of Tokyo and Tokyo Institute of Technology.Read this book now and ace your upcoming coding interview. This is a must read for everyone preparing for Coding Interviews at top companies.

Dynamic Programming For Coding Interviews

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Author : Meenakshi
language : en
Publisher: Notion Press
Release Date : 2017-01-18

Dynamic Programming For Coding Interviews written by Meenakshi and has been published by Notion Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-18 with Computers categories.

I wanted to compute 80th term of the Fibonacci series. I wrote the rampant recursive function, int fib(int n){ return (1==n || 2==n) ? 1 : fib(n-1) + fib(n-2); } and waited for the result. I wait… and wait… and wait… With an 8GB RAM and an Intel i5 CPU, why is it taking so long? I terminated the process and tried computing the 40th term. It took about a second. I put a check and was shocked to find that the above recursive function was called 204,668,309 times while computing the 40th term. More than 200 million times? Is it reporting function calls or scam of some government? The Dynamic Programming solution computes 100th Fibonacci term in less than fraction of a second, with a single function call, taking linear time and constant extra memory. A recursive solution, usually, neither pass all test cases in a coding competition, nor does it impress the interviewer in an interview of company like Google, Microsoft, etc. The most difficult questions asked in competitions and interviews, are from dynamic programming. This book takes Dynamic Programming head-on. It first explain the concepts with simple examples and then deep dives into complex DP problems.

Reinforcement Learning And Dynamic Programming Using Function Approximators

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Author : Lucian Busoniu
language : en
Publisher: CRC Press
Release Date : 2017-07-28

Reinforcement Learning And Dynamic Programming Using Function Approximators written by Lucian Busoniu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-28 with Computers categories.

From household appliances to applications in robotics, engineered systems involving complex dynamics can only be as effective as the algorithms that control them. While Dynamic Programming (DP) has provided researchers with a way to optimally solve decision and control problems involving complex dynamic systems, its practical value was limited by algorithms that lacked the capacity to scale up to realistic problems. However, in recent years, dramatic developments in Reinforcement Learning (RL), the model-free counterpart of DP, changed our understanding of what is possible. Those developments led to the creation of reliable methods that can be applied even when a mathematical model of the system is unavailable, allowing researchers to solve challenging control problems in engineering, as well as in a variety of other disciplines, including economics, medicine, and artificial intelligence. Reinforcement Learning and Dynamic Programming Using Function Approximators provides a comprehensive and unparalleled exploration of the field of RL and DP. With a focus on continuous-variable problems, this seminal text details essential developments that have substantially altered the field over the past decade. In its pages, pioneering experts provide a concise introduction to classical RL and DP, followed by an extensive presentation of the state-of-the-art and novel methods in RL and DP with approximation. Combining algorithm development with theoretical guarantees, they elaborate on their work with illustrative examples and insightful comparisons. Three individual chapters are dedicated to representative algorithms from each of the major classes of techniques: value iteration, policy iteration, and policy search. The features and performance of these algorithms are highlighted in extensive experimental studies on a range of control applications. The recent development of applications involving complex systems has led to a surge of interest in RL and DP methods and the subsequent need for a quality resource on the subject. For graduate students and others new to the field, this book offers a thorough introduction to both the basics and emerging methods. And for those researchers and practitioners working in the fields of optimal and adaptive control, machine learning, artificial intelligence, and operations research, this resource offers a combination of practical algorithms, theoretical analysis, and comprehensive examples that they will be able to adapt and apply to their own work. Access the authors' website at www.dcsc.tudelft.nl/rlbook/ for additional material, including computer code used in the studies and information concerning new developments.

Competitive Programming 2

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Author : Steven Halim
language : en
Publisher:
Release Date : 2011

Competitive Programming 2 written by Steven Halim and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.

Learn C In 7 Days

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Author : Gaurav Aroraa
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-10-06

Learn C In 7 Days written by Gaurav Aroraa and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-06 with Computers categories.

Learn C# in 7 days with practical examples, build a foundation for C# programming, and boost your skills to an advanced level About This Book Learn the basics of C# in 7 days Works as a reference guide describing the major features of C# Build easy and simple code through real-world example scenarios Who This Book Is For The book is for aspiring developers and absolute novices who want to get started with the world of programming. You do not need any knowledge of C# for this book. What You Will Learn Understand and set up the .NET environment Code in C# using the Visual Studio 2017 RC (preferable community edition) IDE Define variables, syntax, control flows, statements, and arrays etc through examples Understand the concepts of Object-Oriented Programming using C# Get acquainted with attributes, collection, generics, and LINQ Get your hands on class members such as Modifiers, Methods, Properties, Indexers, File I/O, Exception Handling, and Regex Build a real-world application using C# 7 In Detail This book takes a unique approach to teach C# to absolute beginners. You'll learn the basics of the language in seven days. It takes a practical approach to explain the important concepts that build the foundation of the C# programming language. The book begins by teaching you the basic fundamentals using real-world practical examples and gets you acquainted with C# programming. We cover some important features and nuances of the language in a hands-on way, helping you grasp the concepts in a fluid manner. Later, you'll explore the concepts of Object-Oriented Programming (OOP) through a real-world example. Then we dive into advanced-level concepts such as generics and collections, and you'll get acquainted with objects and LINQ. Towards the end, you'll build an application that covers all the concepts explained in the book. By the end of this book, you will have next-level skills and a good knowledge of the fundamentals of C#. Style and approach Fast paced guide to get you up-to-speed with the language. Every chapter is followed by an exercise that focuses on building something with the language. The codes of the exercises can be found on the Packt website