Maya 8 Character Modeling (Wordware Applications Library) Review

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(More customer reviews)I'm ammending the rating of 3 out of 5 to 2 out of 5. As I'm continuing with chapter 13 I am finding it rife with bad instructions. When you are trying to learn something as hard as rigging this is the worst thing you can do.
On pages 402-403 the author is saying to lay out your leg joints in the front view. Then on page 406 he's saying to select the two knee joints and rotate them on the Z axis. This makes it swing in an unnatural left to right. If the author had said to layout the joints in the SIDE view then the Z axis would swing like a knee should.
The author tells you to create your spine joints. Then after you've done that select the pelvis joint and Freeze Transformations. This should zero out all the translate values to make it easy to get back to the default position. This does not zero out the translate values, only the rotate & scale.
Also on page 401, instruction 8 tells you to parent neck_2 to the jaw joint. There is no "neck_2" that is the "head" joint you're instructed to create in step 6. SOMEONE from the publisher should check these things before they publish.
Maya is hard enought to learn by itself. Trying to weed through bad instructions make it twice as hard to learn. I can not stand that I paid $45 for a book that is constantly telling me to do the wrong thing.
I'm coming from Maya 4.5 to 8.5. Yes the modeling/sculpting part of the book has been informative. You should NOT use this book if you're learning to rig. The title says what it is good at, Modeling. Get another book for rigging.

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Maya 8 Character Modeling takes a unique approach to modeling as it breaks down character creation using an easy-to-follow formula that makes the learning process less daunting. The author presents an overview of modeling basics and then shows how to block out the body, shape body parts, add details, and create joints and controls using Maya 8. By the time you ve finished the book, you ll have created a figure that is textured, rigged, and ready to be animated.With this book: Understand the building blocks of modeling, including quads, edge loops, normals, UVs, and mapping. Discover how modeling by formula eases the character creation process. Find out how to create a UV layout that makes texturing easier. Learn how to place joints and controls and skin your character so it deforms properly when animated. Companion CD included with the images from the book, Maya files to help build the character, AVI movies that show the modeling process in real time, and Mel scripts for installing a character modeling tool menu that can improve the user s workflow!

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Learning Maya 7: The Modeling and Animation Handbook Review

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(More customer reviews)These books are a spectacular edition. Alias has been good about teaching in their books, but these books actually have FUN projects! I have enough books that will tell me how to do something (and these are VERY easy to understand) but the only ones that I can actually have fun working with are the ones contained in this new series. Not for the advanced user though. If you want advanced, go for the Maya Tecniques series, not the Learning Maya series. Great books!

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This exceptional, full-color Maya Press title -- produced by Alias, the software's creators -- offers a brand-new approach to teaching modeling and animation using the characters from the Academy Award-winning short film The ChubbChubbs. You'll find instructor-led tutorials, scene files, artist interviews, and Maya Personal Learning Edition on the enclosed DVD.

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Process Control: Modeling, Design and Simulation Review

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(More customer reviews)
This book successfully teaches how to analyze dynamic chemical processes and develop automatic control strategies to operate them safely and economically. Rather than simply present theory topics and develop analytical solutions, this textbook uses "interactive learning" through computer-based simulation exercises, employing for this the very popular "Matlab" engineering software package, and the "Simulink" block-diagram simulation environment. Introductions to both "Matlab" and "Simulink" are included in the book.
Each chapter of the book is followed by a series of "learning modules" that serve several purposes: some focus on software tools, while others focus on particular control problems.
An introduction to process control and instrumentation is presented in chapter 1. The development and use of models is very important in control systems engineering, and fundamentals models are developed in chapter 2, including the steady-state solution and linearization to form steady-state models. Chapter 3 focuses on the dynamic behavior of linear systems, starting with state space models and then covering transfer function-based models in detail. Chapter 4 covers the development of empirical models, including continuous and discrete transfer function models.
Chapter 5 provides a detailed introduction to feedback control, developing the basics of feedback systems, PID controllers, and methods of analyzing closed-loop stability. Chapter 6 presents methods for controller tuning. Frequency response analysis techniques, important for determining control system robustness, are presented in chapter 7.
Model-based control leads to improved control loop performance, and one of the clearest model-based techniques (Internal Model Control o IMC) is presented in chapter 8. The PID controller remains the most widely used controller in industry, so chapter 9 is very valuable since it shows how to convert internal model controllers to classical feedback PID controllers.
Chapter 10 develops two widely used control strategies: Cascade and feed-forward control. Chapter 11 presents auto-tuning and gain scheduling, two methods used to deal with poor performance due to changing operating conditions and poor tuned control loops. The phenomenon of reset windup and the development of anti-reset windup strategies are also presented in this chapter.
Chapter 12 presents the split-range, selective, and override control strategies, which are used when we need the control loop to be able of switching between manipulated inputs or select from several measured outputs. Chapter 13 deals with the effect of control loops interactions, while the design of multivariable controllers is developed in chapter 14.
Chapter 15 presents the challenging tasks encountered when developing Plant-wide optimization and control schemes. Chapter 16 presents the most widely applied advanced control strategy: Model Predictive Control (MPC).
Even though the book is designed for Chemical Engineering students, I truly believe that this text would also be suitable for industrial practitioners and students in mechanical, nuclear, industrial, and electrical engineering. I am an Industrial Practitioner of Process Measurement & Control who has been working in the Process Industries for more than 16 years as an Automation, Instrumentation, Process Safety and Process Control Engineer. My academic background is in electrical and electronics engineering (I am an Electronic Engineer), not in chemical engineering as might be the case of the usual reader of this book, but working in the Oil & Gas Industry all this time, I have been dealing with Chemical-Process Control issues in a day-to-day basics. I found this book to be a very useful reference and refresher to gain a better understanding of Modern Process Control Applications.
If you are a practitioner of Process Control you may want to consider also "Instrument Engineers' Handbook, Fourth Edition, Volume Two: Process Control and optimization" by Bela Liptak, for its practical and comprehensive coverage of Process Control.

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Process Control: Modeling, Design, and Simulation is the first complete introduction to process control that fully integrates software tools-helping you master critical techniques hands-on, using MATLAB-based computer simulations. Author B. Wayne Bequette includes process control diagrams, dynamic modeling, feedback control, frequency response analysis techniques, control loop tuning, and start-to-finish chemical process control case studies.

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LightWave 3D 8 Cartoon Character Creation, Volume 1: Modeling & Texturing Review

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(More customer reviews)I got this book a few days ago. After going through it and working with it I think it delivers what it promises: Character Modeling and Texturing. It gives you fairly straight forward information (most of which most users of LW may already know) mixed with fresh news for those of us getting used to animation in Version 8 of LightWave. Having used Lightwave in a different capacity and recently wanting to use it for some character animation - this book was a great help to me. Will it be useful for someone already using Lightwave for character animation? I guess that all depends on your level of expertise. This is not a beginner book (even though it says it starts at that level) mainly because it assumes you know your way around LightWave somewhat. However, people with the talent for picking up software programs will have no problem starting out new.
Like almost all software books it comes with a CD containing project files, plug-ins, etc. You load em. Use em. Etc. I buzzed through the tutorals pretty quick and I gotta say they are easy to follow and thorough without being so basic you feel like you waste half a book getting people up to speed. We have all been there with that disappointment. This book does not do that.
It also does a great job on the process of texturing your models. Now, don't confuse that with how to create textures (there are other books that specialize in that.) What it does show you is how to apply textures to your models properly. In addition are instruction on how to test lighting, rendering and creating QuickTime VR files to view model.
Again, this book is exactly as the title says. If you want to learn everything there is to know about LightWave there are different books to help you. This is not a replacement for a LW manual. However, if you want to learn how to setup some characters for animation and avoid hassels and pitfalls...get this book.


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Character design, modeling, and texturing are the fundamental building blocks of character animation. LightWave 3D [8] Cartoon Character Creation Volume 1: Modeling & Texturing includes both general theory and comprehensive tutorials for every aspect of modeling and texturing 3D characters. Learn how, why, and when to use the most efficient techniques so you can have fun creating your own fantastic 3D characters.Find out how to configure LightWave 3D for character creation, and learn the necessary steps of the character concept, design, and planning stages. Discover multiple methods for modeling characters and clothing using subdivision patches. Understand the techniques for creating complex UV mapping. Learn about surface attributes and surfacing characters. Enhance the appearance of your characters through the use of gradients and procedural textures. Explore a variety of techniques for creating image maps and applying them to your characters.

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Database Modeling & Design: The Fundamental Principles (Morgan Kaufmann Series in Data Management Systems) Review

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(More customer reviews)Why waste your time reading 600+ pages to learn how to create a database? You can read this book and it is less than 300 pages! It covers everything. I recommend this book to anyone that wants to know what makes a great relational database work regardless of the DBMS. This is for beginners wanting to learn for the first time to those with DB experience that want a refresher on the fundamentals!

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Introduction To Three-dimensional Climate Modeling Review

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(More customer reviews)While this isn't a complete introduction, and while it may inevitably be slightly out of date, this is nonetheless the best introduction to climate modeling I've found. It presents the primary methods, and discusses the accomplishments and shortcomings of the field honestly (if at times a bit defensively).
There are clear limitations to climate modeling. For anyone with training in more mainstream Artificial Intelligence techniques, it's very uncomfortable to "test on the training data," which is exactly what climate modelers must do (i.e., they must run their models on the recent past, and if their models don't perform well on it, they will be tweaked until they do--effectively "cheating" because fidelity to the recent past is obviously no indication of predictive power if you tweak the model specifically to work on the recent past). Much of the uncertainty comes from sub-grid interactions that must be parameterized. For example, the formation of clouds is still an area of great uncertainty, and yet has an enormous effect on the climate. The authors recognize this issue, and identify it as a field where future research should focus.
On the other hand, climate modeling has been extremely useful as an inspiration to the imagination, and in working out the logical implications of what we currently believe to be true (both through those things that can be tested in a lab, like the absorption spectrum of carbon dioxide, or those that need to be parameterized, like cloud formation). We can't predict the future, but models allow us to get a sense of what may happen.
The authors discuss all of this, and illustrate it throughout. Of course, as scientists who have spent their lives in climate modeling, they are as supportive of climate modeling as one might expect. But they are also good scientists, and therefore open about the shortcomings.
In short, I'd recommend this book to anyone who wants an introduction to climate modeling. It's a fascinating and important subject that more people should know more about.

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This book provides an introduction to the development of three-dimensional climate models, including their four major components: atmosphere, ocean, land/vegetation, and sea ice. The fundamental processes in each component and the interactions among them are explained using basic scientific principles, and elements of the numerical methods used in solving the model equations are also provided. The authors show how the theory and models grew historically and how well they are able to account for known aspects of the climate system. This book is written so that a reader who is only vaguely aware of climate models will be able to gain an understanding of what the models are attempting to simulate, how the models are constructed, what the models have succeeded in simulating, and how the models are being used. Examples illustrating the use of the models to simulate aspects of the current climate system are followed by examples illustrating the application of the models to important scientific areas such as understanding paleoclimates, the last millennium, the El Nino/Southern Oscillation, and the effects of increasing greenhouse gas concentrations on future climate change. The book is appropriate for scientists, graduate students, and upper-level undergraduates and can be used as a textbook or for self study and reference. The authors have considerably updated the book from the first edition by adding descriptions of many techniques and results developed since the mid-1980s.

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The Microguide to Process Modeling in BPMN Review

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(More customer reviews)I like the idea the authors had about a micro guide, sometimes these topics can be daunting and offering a book that can be read in a day to get up to speed is a great idea. There are some possible improvements and not necessarily criticisms, the flow of the book could use some improvement, In some chapters a topic is introduced at the beginning but then the authors go off on a tangent though relevant I found myself going back and rereading the start of the chapter thinking I had missed something only to find that topic discussed towards the end. I think the best improvement they could have made was to use consistent real life modeling examples, early in the book the authors suggest they will explore some common archetypes and then list them with participants and sub processes but then use examples like making a PBJ sandwich instead of using any of the processes they mentioned. The authors also introduce what they call the Process Modeling framework which makes sense and is a common approach sadly they describe the PMF sequence but never delve into an example that shows a process being modeled from start to finish, though I followed I think a example would have really helped.
Overall I recommend the book and hopefully the authors will update it, certainly I would consider it as a standard book for our analysts but will wait to see if any of the above get addressed.


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With over fifty implementations, Business Process Modeling Notation (BPMN) is an increasingly successful Object Management Group (OMG) standard. Whether you are in government, manufacturing, or business, you can easily and accurately depict your company's processes in BPMN. BPMN Specification 1.1, however, can be abstract, lengthy, and complicated. As a result, learning to use BPMN can be daunting and force professionals to steer clear of it without an efficient and easy way of getting acquainted with the material. The straightforward information that is packed into this book is exactly what is needed. This guide gathers all the ideas, design, and problem-solving of BPMN into one simple, focused book, and offers concrete true-life examples that explain BPMN's approach to process modeling.

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Functions Modeling Change: A Preparation for Calculus Review

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(More customer reviews)Great book! It is especially good for understanding what different functions do, and how. This is very important for understanding calculus. Great examples, always linking functions with things in real life.

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From the Calculus Consortium based at Harvard University, this comprehensible book prepares readers for the study of calculus, presenting families of functions as models for change. These materials stress conceptual understanding and multiple ways of representing mathematical ideas.

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Principles and Practice of Structural Equation Modeling Review

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(More customer reviews)Rex Kline easy writing style will take you through step-by-step in one of the most comprehesive yet accessible introductions to multivariate analysis and structural equation modeling. After outlining the building blocks of SEM (multiple regression, path analysis, and factor analysis), Kline gets the reader ready to tackle popular SEM software with examples for AMOS, LISREL and EQS. There is also a great chapter on what NOT to do with this often misused technique. For a preview, see Kline's article in the Journal of Clinical Psychology (1991), Latent variable path analysis: A beginner's tour guide. This book is an excellent read, and a must have for researchers and statisticians.

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Designed for students and researchers without an extensive quantitative background, this book offers an informative guide to the application, interpretation, and pitfalls of structural equation modeling (SEM) in the social sciences. This is an accessible volume which covers introductory techniques, including path analysis and confirmatory factor analysis, and provides an overview of more advanced methods, such as the evaluation of nonlinear effects, the analysis of means in covariance structure models, and latent growth models for longitudinal data. Providing examples from various disciplines to illustrate all aspects of SEM, the author offers clear instructions on the preparation and screening of data, common mistakes to avoid, and features of widely used software programs (Amos, EQS, and LISREL). Readers will acquire the skills necessary to begin to use SEM in their own research and to interpret and critique the use of the method by others.

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Probability, Markov Chains, Queues, and Simulation: The Mathematical Basis of Performance Modeling Review

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(More customer reviews)This is the most succinct, clear mathematics book I have ever own. Unlike many mathematics books whose mathematical derivations usually have several missing yet important steps make people scratching their heads, this books is not one of them. All the derivations are very detailed along with great explanations and numerical examples. It is a rare gem in mathematical literature and I salute Prof. Stewart for his great achievement.

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Probability, Markov Chains, Queues, and Simulation provides a modern and authoritative treatment of the mathematical processes that underlie performance modeling. The detailed explanations of mathematical derivations and numerous illustrative examples make this textbook readily accessible to graduate and advanced undergraduate students taking courses in which stochastic processes play a fundamental role. The textbook is relevant to a wide variety of fields, including computer science, engineering, operations research, statistics, and mathematics.

The textbook looks at the fundamentals of probability theory, from the basic concepts of set-based probability, through probability distributions, to bounds, limit theorems, and the laws of large numbers. Discrete and continuous-time Markov chains are analyzed from a theoretical and computational point of view. Topics include the Chapman-Kolmogorov equations; irreducibility; the potential, fundamental, and reachability matrices; random walk problems; reversibility; renewal processes; and the numerical computation of stationary and transient distributions. The M/M/1 queue and its extensions to more general birth-death processes are analyzed in detail, as are queues with phase-type arrival and service processes. The M/G/1 and G/M/1 queues are solved using embedded Markov chains; the busy period, residual service time, and priority scheduling are treated. Open and closed queueing networks are analyzed. The final part of the book addresses the mathematical basis of simulation.

Each chapter of the textbook concludes with an extensive set of exercises. An instructor's solution manual, in which all exercises are completely worked out, is also available (to professors only).

Numerous examples illuminate the mathematical theories
Carefully detailed explanations of mathematical derivations guarantee a valuable pedagogical approach
Each chapter concludes with an extensive set of exercises

Professors: A supplementary Solutions Manual is available for this book. It is restricted to teachers using the text in courses. For information on how to obtain a copy, refer to: http://press.princeton.edu/class_use/solutions.html

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Two-Sided Matching: A Study in Game-Theoretic Modeling and Analysis (Econometric Society Monographs) Review

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(More customer reviews)This book is totally dedicated to matching theory. The book in itself is rather general, it doesn't focus on any particular application, and discusses matching as a general abstract theory. Therefore the book can be used by both micro- and macro people equally. It basically covers the problem of one-to-one and one-to-many matchings and tries to explain when equilibriums exist and if matches are unique or non-unique and comes with algorithms or constructive methods to actually do the matching. The structure of the book is mostly like math books and at each step presents an algorithm or a theorem or lemma that states a result. In most cases the proof comes afterwards. However this doesn't undermine the practicality of the book as you can easily locate the algorithm or theorem that embodies your required result and just use it. In my opinion this is one of those books you want to keep on your shelf and refer to every now and then when need be.

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Two-sided matching provides a model of search processes such as those between firms and workers in labor markets or between buyers and sellers in auctions. This book gives a comprehensive account of recent results concerning the game-theoretic analysis of two-sided matching. The focus of the book is on the stability of outcomes, on the incentives that different rules of organization give to agents, and on the constraints that these incentives impose on the ways such markets can be organized. The results for this wide range of related models and matching situations help clarify which conclusions depend on particular modeling assumptions and market conditions, and which are robust over a wide range of conditions.

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Exploring 3D Modeling with Cinema 4D R9 (Design Exploration) Review

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(More customer reviews)This is the best book to not only give you the basics of C4D but of 3-D in general.
It does not give you the really advanced techniques but gives you a great basic understanding of what makes the program tick. The book's explore and trial and
error technique to learning seems a much better approach than some other books
and tutorials. They just give you the steps in doing somthing but don't explain what they do so you are left with little understanding of what you did. Tony shows the
concepts and then gives you ways to experiment with the concepts and solidify
your understanding. I am a 2-D designer learning 3-D and the book makes the program exceptionally understandable.

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In his much-anticipated new book, veteran 3D modeling and animation expert Tony Alley introduces the key concepts of building scenes and models usingthe latest release of Maxon's Cinema 4D, a 3D program embraced by the design community for putting the focus on creative production rather than on learning complex software.Explaining the technology in clear, design-oriented terms, Exploring 3D Modeling with Cinema 4D V9 covers basic modeling techniques, working with materials and textures, lighting, and, rendering.Throughout, the emphasis is on how designers can use Cinema 4D to meet client needs with eye catching scenes and models while exploring their own artistic impulses.Cinema 4D continues to grow in power and popularity in the design community.Its highly customizable graphic user interface is especially easy to learn and makes the software a solid choice for 2D designers making the transition to 3D and for those individuals new to graphic design, computer graphics or 3D.

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Autocad 2007 3-D Modeling, a Visual Approach Review

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(More customer reviews)This is a great book! I think injustice is done if you rate it low! I rate it 5 stars because it is a resourceful book for learning or teaching 3D CAD. I am using it as a textbook in my AutoCad 3D class and both myself and the students appreciate the organization, samples and exercises of the book. The accompanying CD Rom is good: it provides the exercises and samples drawn in the book.
I enjoyed that book a lot!
For a long time I was searching for a good resource book for teaching 3D CAD and I finally got what I wanted with this book.
So far, comparing to other 3D CAD books I have seen in the market this is the best.
PS: I have ordered many issues of this book for my students and so far I have not had any problem with opening the CD from its sealed envelope.

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This completely up-to-date book is the perfect means for learning to use the three-dimensional capabilities of AutoCAD 2007!It boasts a hands-on introduction to more than 70 AutoCAD commands relating to 3D space and 3D modeling, with concise and easy-to-understand instructions helping users get the most out of every 3D feature of AutoCAD.A series of self-paced tutorials at the end of most chapters guide readers through the hands-on completion of various 3D wireframe, surface, and solid models.An accompanying CD with drawing files of 3D models gets readers up and running quickly.

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Regression Modeling: Methods, Theory, and Computation with SAS Review

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(More customer reviews)As a doctoral student in public health, I am always looking for more texts to add to my professional library in statistics. This book not only covers some of the basic regression methods, but also many of the much more advanced methods that I have in classes. I really like how this text explains simply the ideas behind the different methods and when to use, as well as the SAS code and the explanation of the SAS code and output. The only downside is that I think the index could be a little longer - sometimes it is difficult to find a particular model though it actually is in the text.

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Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques using SAS to solve a wide variety of regression problems. The author fully documents the SAS programs and thoroughly explains the output produced by the programs.The text presents the popular ordinary least squares (OLS) approach before introducing many alternative regression methods. It covers nonparametric regression, logistic regression (including Poisson regression), Bayesian regression, robust regression, fuzzy regression, random coefficients regression, L1 and q-quantile regression, regression in a spatial domain, ridge regression, semiparametric regression, nonlinear least squares, and time-series regression issues. For most of the regression methods, the author includes SAS procedure code, enabling readers to promptly perform their own regression runs. A Comprehensive, Accessible Source on Regression Methodology and ModelingRequiring only basic knowledge of statistics and calculus, this book discusses how to use regression analysis for decision making and problem solving. It shows readers the power and diversity of regression techniques without overwhelming them with calculations.

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Biomedical Signal Processing and Signal Modeling Review

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(More customer reviews)Good book for looking at the mathematics behind biomedical signal processing. If your going to use Matlab in conjunction with your study of this book, I used "Biosignal and Biomedical Image Processing: Matlab-Based Applications," by John L. Semmlow.

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A biomedical engineering perspective on the theory, methods, and applications of signal processing This book provides a unique framework for understanding signal processing of biomedical signals and what it tells us about signal sources and their behavior in response to perturbation. Using a modeling-based approach, the author shows how to perform signal processing by developing and manipulating a model of the signal source, providing a logical, coherent basis for recognizing signal types and for tackling the special challenges posed by biomedical signals-including the effects of noise on the signal, changes in basic properties, or the fact that these signals contain large stochastic components and may even be fractal or chaotic. Each chapter begins with a detailed biomedical example, illustrating the methods under discussion and highlighting the interconnection between the theoretical concepts and applications. The author has enlisted experts from numerous subspecialties in biomedical engineering to help develop these examples and has made most examples available as Matlab or Simulink files via anonymous ftp. Without the need for a background in electrical engineering, readers will become acquainted with proven techniques for analyzing biomedical signals and learn how to choose the appropriate method for a given application.
An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the author.

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Modeling and Simulation of Dynamic Systems Review

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(More customer reviews)I have taken the Modeling course at UT Arlington with Dr. Woods (the author), the book covers modeling techniques for Electrical, mechanical, heat tranfer..systems. it has a practical review of differenitial equations. Also has Practical simulation information. and it is great to keep as a reference.

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This book reflects the state-of-the-art and current trends in modeling and simulation. The book provides comprehensive coverage of 1) the modeling techniques of the major types of dynamic engineering systems, 2) the solution techniques for the resulting differential equations for linear and nonlinear systems, and 3) the attendant mathematical procedures related to the presentation of dynamic systems and determination of their time and frequency response characteristics. It explains in detail how to select all of the system component parameter values for static and dynamic performance specifications and limits. For anyone interested in systems dynamics, modeling, and interdisciplinary systems.

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Introduction to Modeling for Biosciences Review

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(More customer reviews)This book is an ideal starting point for undergraduates, postgraduates and even researchers who want to learn the mathematical and computational techniques needed for the modelling of biological systems. The authors cover a wide range of techniques, from analytic approaches (deterministic equations, Markov Chains, master equation) to simulation based ones (agent based models and stochastic simulation algorithms). In particular, I found this book very useful in reviewing various stochastic algorithms needed to simulate biological systems (such as agent based models and Gillespie algorithms), but also in providing Java implementation for the algorithms. The authors' style is clear and this is very helpful for beginners.

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Mathematical modeling can be a useful tool for researchers in the biological scientists.Yet in biological modeling there is no one modeling technique that is suitable for all problems. Instead, different problems call for different approaches. Furthermore, it can be helpful to analyze the same system using a variety of approaches, to be able to exploit the advantages and drawbacks of each. In practice, it is often unclear which modeling approaches will be most suitable for a particular biological question, a problem which requires researchers to know a reasonable amount about a number of techniques, rather than become experts on a single one."Introduction to Modeling for Biosciences" addresses this issue by presenting a broad overview of the most important techniques used to model biological systems.In addition to providing an introduction into the use of a wide range of software tools and modeling environments, this helpful text/reference describes the constraints and difficulties that each modeling technique presents in practice, enabling the researcher to quickly determine which software package would be most useful for their particular problem.Topics and features: introduces a basic array of techniques to formulate models of biological systems, and to solve them; intersperses the text with exercises throughout the book; includes practical introductions to the Maxima computer algebra system, the PRISM model checker, and the Repast Simphony agent modeling environment; discusses agent-based models, stochastic modeling techniques, differential equations and Gillespie's stochastic simulation algorithm; contains appendices on Repast batch running, rules of differentiation and integration, Maxima and PRISM notation, and some additional mathematical concepts; supplies source code for many of the example models discussed, at the associated website http://www.cs.kent.ac.uk/imb/.This unique and practical guide leads the novice modeler through realistic and concrete modeling projects, highlighting and commenting on the process of abstracting the real system into a model.Students and active researchers in the biosciences will also benefit from the discussions of the high-quality, tried-and-tested modeling tools described in the book.Dr. David J. Barnes is a lecturer in computer science at the University of Kent, UK, with a strong background in the teaching of programming.Dr. Dominique Chu is a lecturer in computer science at the University of Kent, UK.He is an internationally recognized expert in agent-based modeling, and has also in-depth research experience in stochastic and differential equation based modeling.

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