Introduction to Stochastic Programming

An introduction to the Java programming language explains how to build complex systems, add tables to graphical interfaces, define layout managers, increase program flexibility, and create network ser

This introduction to programming places computer science in the core of a liberalarts education. Unlike other introductory books, it focuses on the program design process. Thisapproach fosters a varie

The job of the constraint programmer is to use mathematical constraints to model real world constraints and objects. In this book, Kim Marriott and Peter Stuckey provide the first comprehensive intro

Mathematical elegance is a constant theme in this treatment of linear programming and matrix games. Condensed tableau, minimal in size and notation, are employed for the simplex algorithm. In the cont

As an introduction to Python, this book allows readers to take a slow and steady approach to understanding Python code, explaining concepts, connecting programming with real-life examples, writing Python programs, and completing case studies.While there are many books, websites, and online courses about the topic, we break down Python programming into easily digestible lessons of less than 5 minutes each, following our BiteSize approach. Each lesson begins with a clear and short introduction to the topic. This gives you a strong base to start from and gets you ready for deeper learning. Then, you will see coding demonstrations that show the ideas discussed. These examples are simple and useful, helping you really understand the concepts. You'll then practice tasks at different difficulty levels, so you can test your knowledge and increase your confidence. You'll also play with case studies to solve real-world problems. Tips are included to show how you can incorporate generative AI int

Designed for the introductory computing and computer science course, the student-friendly Computer Science Illuminated, Eighth Edition provides students with a solid foundation for further study, and offers non-majors a complete introduction to computing. Fully revised and updated, the eighth edition of this best-selling text retains the accessibility and in-depth coverage of previous editions, while incorporating all-new material on cutting-edge issues in computer science. Authored by the award-winning team Nell Dale and John Lewis, the text provides a unique and innovative layered approach, moving through the levels of computing from an organized, language-neutral perspective. Updated to latest AP CS PrinciplesNew section on cryptocurrencyExpanded coverage of blockchain, cybersecurity attacks, and e-commerceCloud Desktop and companion lab exercises are available on Navigate, which include 23 different lab exercises on topics such as programming, databases, networking, and more

What are the principles behind intelligent systems? How are they built? What are intelligent systems useful for? How do we choose the right tool for the job? These questions are answered by Michael Negnevitsky’s Artificial Intelligence: A Guide to Intelligent Systems.Unlike many books on computer intelligence, which use complex computer science terminology and are crowded with complex matrix algebra and differential equations, this text demonstrates that the ideas behind intelligent systems are simple and straightforward. This text assumes little or no programming experience as it tackles topics like expert systems, fuzzy systems, artificial neural networks, evolutionary computation, knowledge engineering, and data mining.TABLE OF CONTENTS1. Introduction to Intelligent Systems 1.1 Intelligent Machines, or What Machines Can Do 1.2 The History of Artificial Intelligence, or From the ‘Dark Ages’ to Knowledge-based Systems 1.3 Generative AI 1.4 Summary Questions fo

This book offers step-by-step descriptions of various random systems and explores the world of computer simulations. In addition, this book offers a working introduction to those who want to learn how to create and run Monte Carlo simulations. Monte Carlo simulation has been a powerful computational tool for physics models, and when combined with the programming language Excel, this book is a valuable resource for readers who wish to acquire knowledge that can be applied to more complex systems. Visualization of the simulation results via the Visual Basic built in Microsoft EXCEL is presented as the first step towards the subject. Prior experience with the Excel add-in VBA is kept to a minimum. In addition, a chapter on quantum optimization simulation utilizing Python is added to explore the quantum computation. Readers will gain a fundamental knowledge and techniques of simulation physics, which can be extended to STEM projects and other research projects.

《金融數學引論(第二版)》由淺入深、全面系統地介紹金融數學基本理論,著重介紹鞅方法在未定權益定價和對沖中的應用。內容包含離散時間投資組合選擇理論和金融市場模型、Black-Scholes模型及其修正、奇異期權的定價和對沖、Ito過程和擴散過程模型、利率期限結構模型、最優投資組合與投資-消費策略、靜態風險度量。《金融數學引論(第二版)》第四章系統講述了Ito隨機分析理論,這是金融數學中鞅方法的理論基礎。該章內容可以作為概率論研究生學習Ito隨機分析的簡明教材。 本版是在第一版基礎上增加了基於半鞅隨機分析理論的金融數學(共計4章),內容取材於2018年由Springer和科學出版社聯合出版的作者的英文專著Introduction to Stochastic Finance。

The second edition of a rigorous and example-driven introduction to topics in economic dynamics that emphasizes techniques for modeling dynamic systems.This text provides an introduction to the modern theory of economic dynamics, with emphasis on mathematical and computational techniques for modeling dynamic systems. Written to be both rigorous and engaging, the book shows how sound understanding of the underlying theory leads to effective algorithms for solving real-world problems. The material makes extensive use of programming examples to illustrate ideas, bringing to life the abstract concepts in the text. Key topics include algorithms and scientific computing, simulation, Markov models, and dynamic programming. Part I introduces fundamentals and part II covers more advanced material. This second edition has been thoroughly updated, drawing on recent research in the field.New for the second edition:“Programming-language agnostic” presentation using pseudocode.New chapter 1 covering

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 inte

Computational thinking is increasingly gaining importance in modern biology, due to the unprecedented scale at which data is nowadays produced. Bridging the cultural gap between the biological and computational sciences, this book serves as an accessible introduction to computational concepts for students in the life sciences. It focuses on teaching algorithmic and logical thinking, rather than just the use of existing bioinformatics tools or programming. Topics are presented from a biological point of view, to demonstrate how computational approaches can be used to solve problems in biology such as biological image processing, regulatory networks, and sequence analysis. The book contains a range of pedagogical features to aid understanding, including real-world examples, in-text exercises, end-of-chapter problems, colour-coded Python code, and 'code explained' boxes. User-friendly throughout, Computational Thinking for Life Scientists promotes the thinking skills and self-efficacy req

Computational thinking is increasingly gaining importance in modern biology, due to the unprecedented scale at which data is nowadays produced. Bridging the cultural gap between the biological and computational sciences, this book serves as an accessible introduction to computational concepts for students in the life sciences. It focuses on teaching algorithmic and logical thinking, rather than just the use of existing bioinformatics tools or programming. Topics are presented from a biological point of view, to demonstrate how computational approaches can be used to solve problems in biology such as biological image processing, regulatory networks, and sequence analysis. The book contains a range of pedagogical features to aid understanding, including real-world examples, in-text exercises, end-of-chapter problems, colour-coded Python code, and 'code explained' boxes. User-friendly throughout, Computational Thinking for Life Scientists promotes the thinking skills and self-efficacy req

In pioneering work in the 1950s, S. Karlin and J. McGregor showed that probabilistic aspects of certain Markov processes can be studied by analyzing orthogonal eigenfunctions of associated operators. In the decades since, many authors have extended and deepened this surprising connection between orthogonal polynomials and stochastic processes. This book gives a comprehensive analysis of the spectral representation of the most important one-dimensional Markov processes, namely discrete-time birth-death chains, birth-death processes and diffusion processes. It brings together the main results from the extensive literature on the topic with detailed examples and applications. Also featuring an introduction to the basic theory of orthogonal polynomials and a selection of exercises at the end of each chapter, it is suitable for graduate students with a solid background in stochastic processes as well as researchers in orthogonal polynomials and special functions who want to learn about appl

A playful project-based introduction to robot building and programming using the new LEGO MINDSTORMS Robot Inventor Kit. This introduction to the LEGO MINDSTORMS Robot Inventor Kit is a great way to enter the world of robotics--no previous programming experience necessary! Seven cool projects guide you through creating interactive robotic models with the LEGO MINDSTORMS Robot Inventor kit. You'll build a series of funny and increasingly sophisticated models, like: - a remotely-controlled biped walking robot that can transform into a car- a playable 3/4-sized guitar- a fully functional pinball game bigger than the kit box itself- a cute and shy turtle pet with unpredictable behavior- and more! The book is packed with illustrations to help you better visualize each model and includes a quick reference guide to the programming blocks used and the complete bill of materials of the kit, really helpful when developing your own creations. As you build these robots, you'll learn how to use the

Based on the author's forty years of teaching experience, this unique textbook covers both basic and advanced concepts of optimization theory and methods for process systems engineers. Topics covered include continuous, discrete and logic optimization (linear, nonlinear, mixed-integer and generalized disjunctive programming), optimization under uncertainty (stochastic programming and flexibility analysis), and decomposition techniques (Lagrangean and Benders decomposition). Assuming only a basic background in calculus and linear algebra, it enables easy understanding of mathematical reasoning, and numerous examples throughout illustrate key concepts and algorithms. End-of-chapter exercises involving theoretical derivations and small numerical problems, as well as in modeling systems like GAMS, enhance understanding and help put knowledge into practice. Accompanied by two appendices containing web links to modeling systems and models related to applications in PSE, this is an essential

Data Structures using Python provides an introduction to design, analysis, and implementation of data structures using the powerful programming language, Python. This book is designed for a first cour

Dive Into Algorithms is a broad introduction to algorithms using the Python Programming Language.Dive Into Algorithms is a wide-ranging, Pythonic tour of many of the world's most interesting algorithm

The theoretical aspects of the book are based on an essential introduction to the building blocks of the two topics under consideration: mathematical programming and stochastic processes. It also 

The theoretical aspects of the book are based on an essential introduction to the building blocks of the two topics under consideration: mathematical programming and stochastic processes. It also 

Decision-making in the face of uncertainty is a significant challenge in machine learning, and the multi-armed bandit model is a commonly used framework to address it. This comprehensive and rigorous introduction to the multi-armed bandit problem examines all the major settings, including stochastic, adversarial, and Bayesian frameworks. A focus on both mathematical intuition and carefully worked proofs makes this an excellent reference for established researchers and a helpful resource for graduate students in computer science, engineering, statistics, applied mathematics and economics. Linear bandits receive special attention as one of the most useful models in applications, while other chapters are dedicated to combinatorial bandits, ranking, non-stationary problems, Thompson sampling and pure exploration. The book ends with a peek into the world beyond bandits with an introduction to partial monitoring and learning in Markov decision processes.

Now in its second edition, this popular textbook on game theory is unrivalled in the breadth of its coverage, the thoroughness of technical explanations and the number of worked examples included. Covering non-cooperative and cooperative games, this introduction to game theory includes advanced chapters on auctions, games with incomplete information, games with vector payoffs, stable matchings and the bargaining set. This edition contains new material on stochastic games, rationalizability, and the continuity of the set of equilibrium points with respect to the data of the game. The material is presented clearly and every concept is illustrated with concrete examples from a range of disciplines. With numerous exercises, and the addition of a solution manual for instructors with this edition, the book is an extensive guide to game theory for undergraduate through graduate courses in economics, mathematics, computer science, engineering and life sciences, and will also serve as useful re

Specifically designed for linguists, this book provides an introduction to programming using Python for those with little to no experience of coding. Python is one of the most popular and widely-used programming languages as it's also available for free and runs on any operating system. All examples in the text involve language data and can be adapted or used directly for language research. The text focuses on key language-related issues: searching, text manipulation, text encoding and internet data, providing an excellent resource for language research. More experienced users of Python will also benefit from the advanced chapters on graphical user interfaces and functional programming.

Specifically designed for linguists, this book provides an introduction to programming using Python for those with little to no experience of coding. Python is one of the most popular and widely-used programming languages as it's also available for free and runs on any operating system. All examples in the text involve language data and can be adapted or used directly for language research. The text focuses on key language-related issues: searching, text manipulation, text encoding and internet data, providing an excellent resource for language research. More experienced users of Python will also benefit from the advanced chapters on graphical user interfaces and functional programming.

Get ready to code with this easy-to-use series full of projects and tips to get kids programming. Each book in the Ready, Steady Code! series has 4 step-by-step projects with an introduction section (

●ACTIONABLE AND MEASURABLE LEARNING OBJECTIVES EMPHASIZE IMPORTANT CONCEPTS. Newly added learning objectives guide students through the edition, calling attention to critical key points.●SOLID OVERVIEW PRESENTS BREADTH OF COMPUTER SCIENCE WITHOUT PROGRAMMING LANGUAGE SPECIFICS. The authors expertly present a language-independent, breadth-first introduction to computer science that includes coverage of today's hardware, software, and applications as well as a modern view of ethics.●UNIQUE APPROACH INTEGRATES TOPICS USING THE CONCEPT OF ALGORITHMS. Rather than simply present a large collection of seemingly random and unrelated topics, the authors tie the discipline of computer science together using a six-layer hierarchy that clearly demonstrates how the subjects in the book relate to each other. Student gain a clear understanding of the entire discipline of computer science that prepares them for future study in this field.●EXTENSIVE EXERCISES AND PROBLEMS PROVIDE NUMEROUS OPPORTUNITIES

This textbook is ideal for MATLAB/Introduction to Programming courses in both Engineering and Computer Science departments.Engineering Computation with MATLAB introduces the power of computing to engi

Finite-state methods are the most efficient mechanisms for analysing textual and symbolic data, providing elegant solutions for an immense number of practical problems in computational linguistics and computer science. This book for graduate students and researchers gives a complete coverage of the field, starting from a conceptual introduction and building to advanced topics and applications. The central finite-state technologies are introduced with mathematical rigour, ranging from simple finite-state automata to transducers and bimachines as 'input-output' devices. Special attention is given to the rich possibilities of simplifying, transforming and combining finite-state devices. All algorithms presented are accompanied by full correctness proofs and executable source code in a new programming language, C(M), which focuses on transparency of steps and simplicity of code. Thus, by enabling readers to obtain a deep formal understanding of the subject and to put finite-state methods t

Ready to learn how to code a game? Get an introduction to programming with this fun and accessible guide. Learn HTML and JavaScript. Design and build five interactive computer games. Create cool graph

Ready to learn how to code a game? Get an introduction to programming with this fun and accessible guide. Learn HTML and JavaScript. Design and build five interactive computer games. Create cool graph

Build School創辦人暨執行長 吳典璋╱資策會資深講師 王淳平、林俊昌、蘇國鈞 聯合推薦! *增訂版，含微軟Introduction to Programming using HTML and CSS(MTA 98-383)國際認證模擬試題。 *快速上手網頁語法：使用大量範例輔助初學者學習HTML5與CSS，使初學者快速進入網頁開發領域。 *CSS3排版與動畫設計：以實際豐富的案例介紹CSS3特效、排版與動畫技巧。 *訓練JavaScript：從零開始學習JavaScript、由變數宣告、選擇結構、重複結構、陣列到函式，沒有艱澀的專業用詞，讓初學者不在害怕程式設計。 *jQuery互動應用：透過jQuery函式快速選擇元素進行互動、選取表單資料、呼叫動畫函式與替換樣式，打造酷炫的互動網頁。 *RWD響應式網頁：以全新的Bootstrap 4元件建立行動優先的跨平台網頁。 *跨平台行動網頁：建置支援ios,Android,Windows Phone的行動網頁。 *跨平台App設計：使用jQueryMobile與Cordova建製原生Android App，並部署到手機實機上。 *全端應用：整合前端Bootstrap與後端ASP.NET MVC，建製擁有CRUD功能的員工系統。

Many areas of continuum physics pose a challenge to physicists. What are the most general, admissible statistically homogeneous and isotropic tensor-valued random fields (TRFs)? Previously, only the TRFs of rank 0 were completely described. This book assembles a complete description of such fields in terms of one- and two-point correlation functions for tensors of ranks 1 through 4. Working from the standpoint of invariance of physical laws with respect to the choice of a coordinate system, spatial domain representations, as well as their wavenumber domain counterparts are rigorously given in full detail. The book also discusses, an introduction to a range of continuum theories requiring TRFs, an introduction to mathematical theories necessary for the description of homogeneous and isotropic TRFs, and a range of applications including a strategy for simulation of TRFs, ergodic TRFs, scaling laws of stochastic constitutive responses, and applications to stochastic partial differential e

產品特色： 內容包含MTA Python程式語言核心能力國際認證（MTA 98-381 Introduction to Programming Using Python）考試重點的出題方向：變數與資料型態、運算式與運算子、流程控制與迴圈、字元與字串、容器資料型別、函數、模組與工具的操作、疑難排解和錯誤處理、檔案輸入與輸出等。

Whether you are a computer programming student, hobbyist or professional, Lambert's FUNDAMENTALS OF PYTHON™: DATA STRUCTURES, 2E offers the perfect introduction to object-oriented design and data stru

A playful, kid-friendly introduction to game development using Scratch, a visual programming language for making interactive games and animations. Author is a well-known professional game designer.Make Your Own Scratch Games! shows you how to make interactive games using Scratch, a beginner-friendly tool for making and sharing animated games online. Readers use Scratch's block-based programming language to design games from scratch using author's games as examples. Anthropy walks readers through game development process from start to finish, covering everything from mapping out a game's structure, creating animations, and debugging the end product. Readers will understand what makes designing video games challenging and fun, and feel ready to bring their own game ideas to life.

This book explores the fundamentals of computer music and functional programming through the Haskell programming language. Functional programming is typically considered difficult to learn. This introduction in the context of creating music will allow students and professionals with a musical inclination to leverage their experience to help understand concepts that might be intimidating in more traditional computer science settings. Conversely, the book opens the door for programmers to interact with music by using a medium that is familiar to them. Readers will learn how to use the Euterpea library for Haskell (http://www.euterpea.com) to represent and create their own music with code, without the need for other music software. The book explores common paradigms used in algorithmic music composition, such as stochastic generation, musical grammars, self-similarity, and real-time interactive systems. Other topics covered include the basics of signal-based systems in Haskell, sound synt

This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer