20 Best Book For Dynamic Programming (2023 Update)

This is the leading and most up-to-date textbook on the far-ranging algorithmic methodology of dynamic programming, which can be used for optimal control, markovian decision problems, planning and sequential decision making under uncertainty, and discrete/combinatorial optimization. the treatment focuses on basic unifying themes, and conceptual foundations. it illustrates the versatility, power, and generality of the method with many examples and applications from engineering, operations research, and other fields. it also addresses extensively the practical application of the methodology, possibly through the use of approximations, and provides an extensive treatment of the far-reaching methodology of neuro-dynamic programming/reinforcement learning.among its special features, the book 1) provides a unifying framework for sequential decision making, 2) treats simultaneously deterministic and stochastic control problems popular in modern control theory and markovian decision popular in operations research, 3) develops the theory of deterministic optimal control problems including the pontryagin minimum principle, 4) introduces recent suboptimal control and simulation-based approximation techniques (neuro-dynamic programming), which allow the practical application of dynamic programming to complex problems that involve the dual curse of large dimension and lack of an accurate mathematical model, 5) provides a comprehensive treatment of infinite horizon problems in the second volume, and an introductory treatment in the first volume.

This comprehensive study of dynamic programming applied to numerical solution of optimization problems. it will interest aerodynamic, control, and industrial engineers, numerical analysts, and computer specialists, applied mathematicians, economists, and operations and systems analysts.originally published in 1962. the princeton legacy library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of princeton university press. these editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. the goal of the princeton legacy library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by princeton university press since its founding in 1905.

Software development projects can be fun, productive, and even daring. yet they can consistently deliver value to a business and remain under control. extreme programming (xp) was conceived and developed to address the specific needs of software development conducted by small teams in the face of vague and changing requirements. this new lightweight methodology challenges many conventional tenets, including the long-held assumption that the cost of changing a piece of software necessarily rises dramatically over the course of time. xp recognizes that projects have to work to achieve this reduction in cost and exploit the savings once they have been earned. fundamentals of xp include: distinguishing between the decisions to be made by business interests and those to be made by project stakeholders. writing unit tests before programming and keeping all of the tests running at all times. integrating and testing the whole system–several times a day. starting projects with a simple design that constantly evolves to add needed flexibility and remove unneeded complexity. putting a minimal system into production quickly and growing it in whatever directions prove most valuable. why is xp so controversial? some sacred cows don't make the cut in xp: don't force team members to specialize and become analysts, architects, programmers, testers, and integrators–every xp programmer participates in all of these critical activities every day. don't conduct complete up-front analysis and design–an xp project starts with a quick analysis of the entire system, and xpprogrammers continue to make analysis and design decisions throughout development. develop infrastructure and frameworks as you develop your application, not up-front–delivering business value is the heartbeat that drives xp projects. don't write and maintain implementation documentation–communication in xp projects occurs face-to-face, or through efficient tests and carefully written code. you may love xp, or you may hate it, but "extreme programming explained" will force you to take a fresh look at how you develop software. 0201616416b04062001

'one of the best software design books of all time' – bookauthority cory althoff is a self-taught programmer. but once he got there, he realised he was severely under-prepared. he was overwhelmed by the amount of things he needed to know but hadn't learned. his journey learning to program, and his experience in first software engineering job were the inspiration for this book. this book is not just about learning to program, although you will learn to code. if you want to program professionally, it is not enough to learn to code; that is why, in addition to helping you learn to program, althoff also cover the rest of the things you need to know to program professionally that classes and books don't teach you. the self-taught programmer is a roadmap, a guide to take you from writing your first python program to passing your first technical interview. the book is divided into five sections: 1. learn to program in python 3 and build your first program. 2. learn object-oriented programming and create a powerful python program to get you hooked. 3. learn to use tools like git, bash and regular expressions. then use your new coding skills to build a web scraper. 4. study computer science fundamentals like data structures and algorithms. 5. finish with best coding practices, tips for working with a team and advice on landing a programming job. you can learn to program professionally. the path is there. will you take it? from the author i spent one year writing the self-taught programmer. it was an exciting and rewarding experience. i treated my book like a software project. after i finished writing it, i created a program to pick out all of the code examples from the book and execute them in python to make sure all 300+ examples worked properly. then i wrote software to add line numbers and color to every code example. finally, i had a group of 200 new programmers 'beta read' the book to identify poorly explained concepts and look for any errors my program missed. i hope you learn as much reading my book as i did writing it. best of luck with your programming!

I wanted to compute 80th term of the fibonacci series. 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.

Expert techniques to make your websites more interactive and engaging in javascript and jquery: interactive front-end development, best-selling author jon duckett delivers a fully illustrated guide to making your websites more interactive and your interfaces more interesting and intuitive. in the book, you’ll explore basic programming concepts that assume no prior knowledge of programming beyond an ability to create a web page using html & css. you’ll use core elements of the javascript language so you can learn how to write your own scripts from scratch, as well as jquery, which will allow you to simplify the process of writing scripts (this is introduced half-way through the book once you have a solid understanding of javascript). you’ll also learn to recreate techniques you have seen on other web sites such as sliders, content filters, form validation, ajax content updates, and much more. each chapter: breaks subjects down into bite-sized chunks with a new topic on each page contains clear descriptions of syntax, each one demonstrated with illustrative code samples uses diagrams and photography to explain complex concepts in a visual way by the end of the book, not only will you be able to use the thousands of scripts, javascript apis, and jquery plugins that are freely available on the web – and be able to customize them – you will also be able to create your own scripts from scratch.

The go-to guide for learning coding from the ground-up adding some coding know-how to your skills can help launch a new career or bolster an old one. coding all-in-one for dummies offers an ideal starting place for learning the languages that make technology go. this edition gets you started with a helpful explanation of how coding works and how it’s applied in the real-world before setting you on a path toward writing code for web building, mobile application development, and data analysis. add coding to your skillset for your existing career, or begin the exciting transition into life as a professional developer—dummies makes it easy. learn coding basics and how to apply them analyze data and automate routine tasks on the job get the foundation you need to launch a career as a coder add html, javascript, and python know-how to your resume this book serves up insight on the basics of coding, designed to be easy to follow, even if you’ve never written a line of code in your life. you can do this.

With the same insight and authority that made their book the unix programming environment a classic, brian kernighan and rob pike have written the practice of programming to help make individual programmers more effective and productive. the practice of programming is more than just writing code. programmers must also assess tradeoffs, choose among design alternatives, debug and test, improve performance, and maintain software written by themselves and others. at the same time, they must be concerned with issues like compatibility, robustness, and reliability, while meeting specifications. the practice of programming covers all these topics, and more. this book is full of practical advice and real-world examples in c, c++, java, and a variety of special-purpose languages. it includes chapters on: debugging: finding bugs quickly and methodically testing: guaranteeing that software works correctly and reliably performance: making programs faster and more compact portability: ensuring that programs run everywhere without change design: balancing goals and constraints to decide which algorithms and data structures are best interfaces: using abstraction and information hiding to control the interactions between components style: writing code that works well and is a pleasure to read notation: choosing languages and tools that let the machine do more of the work kernighan and pike have distilled years of experience writing programs, teaching, and working with other programmers to create this book. anyone who writes software will profit from the principles and guidance in the practice of programming. 020161586xb04062001

Algorithms are the heart and soul of computer science. their applications range from network routing and computational genomics to public-key cryptography and machine learning. studying algorithms can make you a better programmer, a clearer thinker, and a master of technical interviews. algorithms illuminated is an accessible introduction to the subject for anyone with at least a little programming experience. the exposition emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details—like a transcript of what an expert algorithms tutor would say over a series of one-on-one lessons. part 3 covers greedy algorithms (scheduling, minimum spanning trees, clustering, huffman codes) and dynamic programming (knapsack, sequence alignment, shortest paths, optimal search trees).

Javascript is the programming language of the web and is used by more software developers today than any other programming language. for nearly 25 years this best seller has been the go-to guide for javascript programmers. the seventh edition is fully updated to cover the 2020 version of javascript, and new chapters cover classes, modules, iterators, generators, promises, async/await, and metaprogramming. you'll find illuminating and engaging example code throughout. – this book is for programmers who want to learn javascript and for web developers who want to take their understanding and mastery to the next level. it begins by explaining the javascript language itself, in detail, from the bottom up. it then builds on that foundation to cover the web platform and node.js. – topics include: types, values, variables, expressions, operators, statements, objects, and arrays – functions, classes, modules, iterators, generators, promises, and async/awaitjavascript's standard library: data structures, regular expressions, json, i18n, etc. – the web platform: documents, components, graphics, networking, storage, and threads – node.js: buffers, files, streams, threads, child processes, web clients, and web servers – tools and language extensions that professional javascript developers rely on

R is the world's most popular language for developing statistical software: archaeologists use it to track the spread of ancient civilizations, drug companies use it to discover which medications are safe and effective, and actuaries use it to assess financial risks and keep economies running smoothly.the art of r programming takes you on a guided tour of software development with r, from basic types and data structures to advanced topics like closures, recursion, and anonymous functions. no statistical knowledge is required, and your programming skills can range from hobbyist to pro.along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. you'll also learn to:–create artful graphs to visualize complex data sets and functions–write more efficient code using parallel r and vectorization–interface r with c/c++ and python for increased speed or functionality–find new r packages for text analysis, image manipulation, and more–squash annoying bugs with advanced debugging techniqueswhether you're designing aircraft, forecasting the weather, or you just need to tame your data, the art of r programming is your guide to harnessing the power of statistical computing.

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.

This classic book is an introduction to dynamic programming, presented by the scientist who coined the term and developed the theory in its early stages. bellman introduces his groundbreaking theory and furnishes a new and versatile mathematical tool for the treatment of many complex problems, both within and outside of the discipline. the book is written at a moderate mathematical level, requiring only a basic foundation in mathematics, including calculus. the applications formulated and analyzed in such diverse fields as mathematical economics, logistics, scheduling theory, communication theory, and control processes are as relevant today as they were when bellman first presented them. a new introduction by stuart dreyfus reviews bellman's later work on dynamic programming and identifies important research areas that have profited from the application of bellman's theory.

This classic book is an introduction to dynamic programming, presented by the scientist who coined the term and developed the theory in its early stages. bellman introduces his groundbreaking theory and furnishes a new and versatile mathematical tool for the treatment of many complex problems, both within and outside of the discipline. the book is written at a moderate mathematical level, requiring only a basic foundation in mathematics, including calculus. the applications formulated and analyzed in such diverse fields as mathematical economics, logistics, scheduling theory, communication theory, and control processes are as relevant today as they were when bellman first presented them. a new introduction by stuart dreyfus reviews bellman's later work on dynamic programming and identifies important research areas that have profited from the application of bellman's theory.

Building on what already is the most comprehensive introduction to competitive programming, this enhanced new textbook features new material on advanced topics, such as calculating fourier transforms, finding minimum cost flows in graphs, and using automata in string problems. critically, the text accessibly describes and shows how competitive programming is a proven method of implementing and testing algorithms, as well as developing computational thinking and improving both programming and debugging skills. – compatible with the ioi syllabus, yet also covering more advanced topics, such as maximum flows, nim theory, and suffix structures – surveys specialized algorithms for trees, and discusses the mathematical topics that are relevant in competitive programming – reviews the features of the c++ programming language, and describes how to create efficient algorithms that can quickly process large data sets – discusses sorting algorithms and binary search, and examines a selection of data structures of the c++ standard library – covers such advanced algorithm design topics as bit-parallelism and amortized analysis, and presents a focus on efficiently processing array range queries – describes a selection of more advanced topics, including square-root algorithms and dynamic programming optimization – fully updated, expanded and easy to follow, this core textbook/guide is an ideal reference for all students needing to learn algorithms and to practice for programming contests. knowledge of programming basics is assumed, but previous background in algorithm design or programming contests is not necessary. with its breadth of topics, examples and references, the book is eminently suitable for both beginners and more experienced readers alike. – dr. antti laaksonen has worked as a teacher and researcher at the university of helsinki and aalto university, finland.

The easy way to learn programming fundamentals with python python is a remarkably powerful and dynamic programming language that's used in a wide variety of application domains. some of its key distinguishing features include a very clear, readable syntax, strong introspection capabilities, intuitive object orientation, and natural expression of procedural code. plus, python features full modularity, supporting hierarchical packages, exception-based error handling, and modules easily written in c, c++, java, r, or . net languages, such as c#. in addition, python supports a number of coding styles that include: functional, imperative, object-oriented, and procedural. due to its ease of use and flexibility, python is constantly growing in popularity—and now you can wear your programming hat with pride and join the ranks of the pros with the help of this guide. inside, expert author john paul mueller gives a complete step-by-step overview of all there is to know about python. from performing common and advanced tasks, to collecting data, to interacting with package—this book covers it all! use python to create and run your first application find out how to troubleshoot and fix errors learn to work with anaconda and use magic functions benefit from completely updated and revised information since the last edition if you've never used python or are new to programming in general, beginning programming with python for dummies is a helpful resource that will set you up for success.

Ruby is the fastest growing and most exciting dynamic language out there. this book is the only complete reference for both ruby 1.9 and ruby 2.0, the very latest version of ruby. 2013 marks the 20th anniversary of the ruby language. would you like to go from first idea to working code much, much faster? do you currently spend more time satisfying the compiler instead of your clients or end users? are you frustrated with demanding languages that seem to get in your way, instead of getting the work done? are you using rails, and want to dig deeper into the underlying ruby language? ruby is a fully object-oriented language, much like the classic object-oriented language, smalltalk. like smalltalk, it is dynamically typed (as opposed to java or c++), but unlike smalltalk, ruby features the same conveniences found in modern scripting languages such as perl and python. the combination of the power of a pure object-oriented language with the convenience of a scripting language makes ruby a favorite tool of intelligent, forward-thinking programmers. the pickaxe contains four major sections: an acclaimed tutorial on using ruby. the definitive reference to the language. complete documentation of all built-in classes, modules, and methods. complete descriptions of all 97 standard libraries. this is the reference manual for ruby, including a description of all the standard library modules, a complete reference to all built-in classes and modules (including all the new and changed methods introduced by ruby 1.9, 1.9.2, 1.9.3, and 2.0). it also includes all the new and changed syntax and semantics introduced since ruby 1.8. learn about the new parameter passing rules, local variable scoping in blocks, fibers, and the new block declaration syntax, among other exciting new features. about ruby 2.0 ruby 2.0 is a minor update to ruby 1.9, unlike the more major updates from ruby 1.8 to ruby 1.9. the major language changes in ruby 2.0 are the addition of keyword arguments and the change to use utf-8 as the default source file encoding. there are a number of additions to the standard library, including: @enumerator::lazy@, which adds support for lazy access to potentially infinite lists. refinements allow you to encapsulate changes to third-party classes, and scope their application to individual source files, preventing your changes from polluting the global application. you'll also find that ruby 2 is faster, and has memory management improvements that make it more server-friendly. all told, there are over 110 sections of the book that have been flagged and cross-linked to indicate 2.0 content. what you need this book assumes you have a basic understanding of object-oriented programming. in general, ruby programmers tend to favor the the command line for running their code, and they tend to use text editors rather than ides. * ruby runs on windows, linux, and macs.

A comprehensive look at state-of-the-art adp theory and real-world applications this book fills a gap in the literature by providing a theoretical framework for integrating techniques from adaptive dynamic programming (adp) and modern nonlinear control to address data-driven optimal control design challenges arising from both parametric and dynamic uncertainties. traditional model-based approaches leave much to be desired when addressing the challenges posed by the ever-increasing complexity of real-world engineering systems. an alternative which has received much interest in recent years are biologically-inspired approaches, primarily radp. despite their growing popularity worldwide, until now books on adp have focused nearly exclusively on analysis and design, with scant consideration given to how it can be applied to address robustness issues, a new challenge arising from dynamic uncertainties encountered in common engineering problems. robust adaptive dynamic programming zeros in on the practical concerns of engineers. the authors develop radp theory from linear systems to partially-linear, large-scale, and completely nonlinear systems. they provide in-depth coverage of state-of-the-art applications in power systems, supplemented with numerous real-world examples implemented in matlab. they also explore fascinating reverse engineering topics, such how adp theory can be applied to the study of the human brain and cognition. in addition, the book: covers the latest developments in radp theory and applications for solving a range of systems’ complexity problems explores multiple real-world implementations in power systems with illustrative examples backed up by reusable matlab code and simulink block sets provides an overview of nonlinear control, machine learning, and dynamic control features discussions of novel applications for radp theory, including an entire chapter on how it can be used as a computational mechanism of human movement control robust adaptive dynamic programming is both a valuable working resource and an intriguing exploration of contemporary adp theory and applications for practicing engineers and advanced students in systems theory, control engineering, computer science, and applied mathematics.

Endless loop chronicles the complete history of the basic programming language–from its humble beginnings at dartmouth college, to its widespread adoption and dominance in education, to its decline and subsequent modern rebirth. in the early morning hours of may 1, 1964, dartmouth college birthed fraternal twins: basic, the beginner's all-purpose symbolic instruction code programming language, and, simultaneously, the dartmouth time-sharing system (dtss). it hadn't been an easy birth, and the gestation period was likewise difficult. basic was primarily the idea of one man, mathematics professor john kemeny, a brilliant hungarian mathematician who had once been an assistant to albert einstein, while the dtss satisfied the vision of another, mathematics and statistics professor thomas kurtz, who had brought a democratizing spirit to dartmouth's campus in the form of free computing for all. basic and dtss caught on at dartmouth quickly, with a vast majority of undergraduates (and faculty) making use of the computer system via teletypewriters only several years after its inception. but by the early 1970s, with the personal computer revolution fast approaching, kemeny and kurtz began to lose control over basic as it achieved widespread popularity outside of dartmouth. the language was being adapted to run on a wide variety of computers, some much too short of memory to contain the full set of dartmouth basic features. most notably, microsoft built its business on the back of rom-based basic interpreters for a variety of microcomputers. although the language was ubiquitous in schools by the early 1980s, it came under attack by such notables as computer scientist edsger w. but by then it was too late: the era of basic's global dominance was over. in endless loop, author mark jones lorenzo documents the history and development of dartmouth basic, true basic, tiny basic, microsoft basic–including altair basic, applesoft basic, color basic, commodore basic, trs-80 level ii basic, ti basic, ibm basica/gw-basic, quick – basic/qbasic, visual basic, and small basic–as well as 9845 basic, atari basic, bbc basic, cbasic, locomotive basic, mac – basic, qb64, simons' basic, sinclair basic, super – basic, and turbo basic/power – basic, among a number of other implementations. the ascendance of basic paralleled the emergence of the personal computer, so the story of basic is first and foremost a story–actually, many interlocking stories–about computers. but it is also a tale of talented people who built a language out of a set of primal ingredients: sweat, creativity, rivalry, jealousy, cooperation, and plain hard work, and then set the language loose in a world filled with unintended consequences. how those unintended consequences played out, leading to the demise of the most popular computer language the world has ever known, is the focus of endless loop.

Learn intel 64 assembly language and architecture, become proficient in c, and understand how the programs are compiled and executed down to machine instructions, enabling you to write robust, high-performance code. – low-level programming explains intel 64 architecture as the result of von neumann architecture evolution. the book teaches the latest version of the c language (c11) and assembly language from scratch. it covers the entire path from source code to program execution, including generation of elf object files, and static and dynamic linking. code examples and exercises are included along with the best code practices. optimization capabilities and limits of modern compilers are examined, enabling you to balance between program readability and performance. the use of various performance-gain techniques is demonstrated, such as sse instructions and pre-fetching. relevant computer science topics such as models of computation and formal grammars are addressed, and their practical value explained. – what you'll learn – low-level programming teaches programmers to:freely write in assembly language – understand the programming model of intel 64write maintainable and robust code in c11follow the compilation process and decipher assembly listings – debug errors in compiled assembly code – use appropriate models of computation to greatly reduce program complexity – write performance-critical code – comprehend the impact of a weak memory model in multi-threaded applications – who this book is for – intermediate to advanced programmers and programming students