Answers.Body: <h2>Why is AIMA dense?</h2>
  <p>Artificial intelligence is a broad field: that's why <a href="http://aima.cs.berkeley.edu/" rel="nofollow noreferrer">Artificial Intelligence: A Modern Approach</a> (AIMA) may look a bit dense to newcomers, given that it covers many different aspects of AI, such as search, machine learning, and natural language processing.</p>
  <hr />
  <h2>AI is not just ML!</h2>
  <p>The first book in <a href="https://ai.stackexchange.com/a/7658/2444">this answer</a> is a good book, but it focuses on <a href="https://ai.stackexchange.com/q/7446/2444">computational intelligence</a> approaches, which are often considered part of AI too. The other books that you mention in your post also focus on subfields of AI, such as <a href="https://ai.stackexchange.com/q/35/2444">machine learning</a> or image processing, so they do not cover all aspects of AI.</p>
  <hr />
  <h2>Alternatives to AIMA</h2>
  <div class="s-table-container"><table class="s-table">
  <thead>
  <tr>
  <th>Title</th>
  <th>Author(s)</th>
  <th>Year</th>
  <th>Topics</th>
  <th>Comments</th>
  </tr>
  </thead>
  <tbody>
  <tr>
  <td><a href="https://courses.csail.mit.edu/6.034f/ai3/rest.pdf" rel="nofollow noreferrer">Artificial intelligence</a></td>
  <td>Patrick Winston</td>
  <td>1992 (3rd edition)</td>
  <td>Search, rule-based systems, machine learning, evolutionary algorithms, etc.</td>
  <td>I occasionally consulted this book; <a href="https://news.mit.edu/2019/patrick-winston-professor-obituary-0719" rel="nofollow noreferrer">Patrick Winston was a professor at MIT and also director of the AI Lab at MIT</a>; you can also find his free course on Artificial Intelligence (which I highly recommend) <a href="https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/" rel="nofollow noreferrer">here</a>.</td>
  </tr>
  <tr>
  <td><a href="https://www.sciencedirect.com/book/9781558604674/artificial-intelligence-a-new-synthesis" rel="nofollow noreferrer">Artificial Intelligence: A New Synthesis</a></td>
  <td><a href="https://ai.stanford.edu/%7Enilsson/" rel="nofollow noreferrer">Nils J. Nilsson</a></td>
  <td>1998</td>
  <td>Neural networks, evolutionary algorithms, search, knowledge representation and reasoning, planning, Bayesian networks, etc.</td>
  <td>Nilsson also wrote other important books related to AI and the philosophy of AI, such as <a href="https://ai.stanford.edu/%7Enilsson/QAI/qai.pdf" rel="nofollow noreferrer">The Quest for Artificial Intelligence: A History of Ideas and Achievements</a> (2009), among other important contributions to the AI field, such as <a href="https://ai.stanford.edu/%7Enilsson/Shakey.mp4" rel="nofollow noreferrer">the robot <em>Shakey</em></a> and <a href="https://apps.dtic.mil/sti/pdfs/ADA459687.pdf" rel="nofollow noreferrer"><em>STRIPS</em></a>.</td>
  </tr>
  <tr>
  <td><a href="http://www.academia.dk/BiologiskAntropologi/Epidemiologi/DataMining/Artificial_Intelligence-A_Guide_to_Intelligent_Systems.pdf" rel="nofollow noreferrer">Artificial Intelligence: A Guide to Intelligent Systems</a></td>
  <td><a href="https://scholar.google.com/citations?user=XXsqjkgAAAAJ&amp;hl=en" rel="nofollow noreferrer">Michael Negnevitsky</a></td>
  <td>2005 (2nd edition)</td>
  <td>Expert systems, fuzzy systems, artificial neural networks, evolutionary computation, hybrid systems, etc.</td>
  <td></td>
  </tr>
  <tr>
  <td><a href="http://www.uoitc.edu.iq/images/documents/informatics-institute/exam_materials/artificial%20intelligence%20structures%20and%20strategies%20for%20%20complex%20problem%20solving.pdf" rel="nofollow noreferrer">Artificial Intelligence: Structures and Strategies for Complex Problem Solving</a></td>
  <td>George Lugar</td>
  <td>2009 (6th edition)</td>
  <td>History of AI, search, knowledge representation, expert systems, rule-based systems, machine learning, evolutionary algorithms, automated reasoning, natural language understanding, etc.</td>
  <td>This book is mentioned by Ben Goertzel in his paper <a href="https://sciendo.com/article/10.2478/jagi-2014-0001" rel="nofollow noreferrer">Artificial General Intelligence: Concept, State of the Art, and Future Prospects</a> as a &quot;popular AI textbook&quot;.</td>
  </tr>
  <tr>
  <td><a href="https://artint.info/2e/html/ArtInt2e.html" rel="nofollow noreferrer">Artificial Intelligence: Foundations of Computational Agents</a></td>
  <td>David L. Poole, Alan K. Mackworth</td>
  <td>2017 (2nd edition)</td>
  <td>Machine learning, search, planning, reasoning, and knowledge-based systems, etc.</td>
  <td>I occasionally consulted this book.</td>
  </tr>
  </tbody>
  </table></div>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-01-16T19:10:30.483Z
Answers.LastActivityDate: 2024-12-27T15:32:14.233Z
Answers.LastEditDate: 2024-12-27T15:32:14.233Z
Answers.UserDisplayName: nbro
Answers.Body: <p>The following 2 books helped me understand the basics and guided me through my first AI / CI implementations.</p>
  <ul>
  <li><p><a href="http://www.shahed.ac.ir/stabaii/Files/CompIntelligenceBook.pdf" rel="nofollow noreferrer"><strong>Computational Intelligence: An Introduction</strong></a> by Andries P. Engelbrecht</p>
  <p>It includes the most relevant developments in computational intelligence with good discussions on intelligence and artificial intelligence (AI).</p>
  </li>
  <li><p><a href="https://www.elsevier.com/books/computational-intelligence/eberhart/978-1-55860-759-0" rel="nofollow noreferrer"><strong>Computational Intelligence: Concepts to Implementation</strong></a> by Russell C. Eberhart and Yuhui Shi</p>
  <p>It is a comprehensive textbook, supported with lots of practical examples.</p>
  </li>
  </ul>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2018-08-21T08:50:39.953Z
Answers.LastActivityDate: 2021-01-16T20:21:37.610Z
Answers.LastEditDate: 2021-01-16T20:21:37.610Z
Answers.UserDisplayName: D. S.
Body: <p>There are two textbooks that I most love and am most afraid of in the world: <em>Introduction to Algorithms by Cormen</em> et al. and <em>Artificial Intelligence: A Modern Approach by Norvig</em> et al. I have started the "AI: A Modern Approach" more than once, but the book is so dense and full of theory that I get discouraged after a couple of weeks and stop.</p>
  
  <p><strong>I am looking for a similar AI book but with an equal emphasis on theory and practice.</strong> Some examples of what I am looking for:</p>
  
  <ul>
  <li><p>The Elements of Statistical Learning by Tibshirani et al. <strong>(detailed theory)</strong></p></li>
  <li><p>An Introduction to Statistical Learning: With Applications in R by
  Tibshirani et al. <strong>(theory+practical)</strong></p></li>
  <li>Digital Image Processing by Gonzalez et al. <strong>(detailed theory)</strong></li>
  <li>Digital Image Processing Using MATLAB by Gonzalez et al.
  <strong>(theory+practical)</strong></li>
  </ul>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-01-16T23:53:30.420Z
Comments.Text: As nbro mentioned in his answer, Russell and Norvig is relatively broad, because it is meant as an introduction to all of AI, rather than an introduction to specific subfields (such as statistical/machine learning, etc.).
Comments.UserDisplayName: The Pointer
Tags: <reference-request><norvig-russell><books>
Title: What are some alternatives to the book "Artificial Intelligence: A Modern Approach"?
UserDisplayName: ml_nrd
ThreadText: # What are some alternatives to the book "Artificial Intelligence: A Modern Approach"?
  
  (Asked by: username_0 on 2018-04-11)
  
  There are two textbooks that I most love and am most afraid of in the world: *Introduction to Algorithms by Cormen* et al. and *Artificial Intelligence: A Modern Approach by Norvig* et al. I have started the "AI: A Modern Approach" more than once, but the book is so dense and full of theory that I get discouraged after a couple of weeks and stop.
  
  **I am looking for a similar AI book but with an equal emphasis on theory and practice.** Some examples of what I am looking for:
  
  * The Elements of Statistical Learning by Tibshirani et al. **(detailed theory)**
  * An Introduction to Statistical Learning: With Applications in R by
    Tibshirani et al. **(theory+practical)**
  * Digital Image Processing by Gonzalez et al. **(detailed theory)**
  * Digital Image Processing Using MATLAB by Gonzalez et al.
    **(theory+practical)**
  
  **Tags:** reference-request, norvig-russell, books
  
  > **Comments:**
  > **username_1**: As username_2 mentioned in his answer, Russell and Norvig is relatively broad, because it is meant as an introduction to all of AI, rather than an introduction to specific subfields (such as statistical/machine learning, etc.).  
  
  ---
  
  ## 2 answers
  
  ### Answer by username_2 on 2021-01-16. Score: 6
  
  ## Why is AIMA dense?
  
  Artificial intelligence is a broad field: that's why [Artificial Intelligence: A Modern Approach](http://aima.cs.berkeley.edu/) (AIMA) may look a bit dense to newcomers, given that it covers many different aspects of AI, such as search, machine learning, and natural language processing.
  
  ---
  
  ## AI is not just ML!
  
  The first book in [this answer](https://ai.stackexchange.com/a/7658/2444) is a good book, but it focuses on [computational intelligence](https://ai.stackexchange.com/q/7446/2444) approaches, which are often considered part of AI too. The other books that you mention in your post also focus on subfields of AI, such as [machine learning](https://ai.stackexchange.com/q/35/2444) or image processing, so they do not cover all aspects of AI.
  
  ---
  
  ## Alternatives to AIMA
  
  | Title | Author(s) | Year | Topics | Comments |
  | --- | --- | --- | --- | --- |
  | [Artificial intelligence](https://courses.csail.mit.edu/6.034f/ai3/rest.pdf) | Patrick Winston | 1992 (3rd edition) | Search, rule-based systems, machine learning, evolutionary algorithms, etc. | I occasionally consulted this book; [Patrick Winston was a professor at MIT and also director of the AI Lab at MIT](https://news.mit.edu/2019/patrick-winston-professor-obituary-0719); you can also find his free course on Artificial Intelligence (which I highly recommend) [here](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/). |
  | [Artificial Intelligence: A New Synthesis](https://www.sciencedirect.com/book/9781558604674/artificial-intelligence-a-new-synthesis) | [Nils J. Nilsson](https://ai.stanford.edu/%7Enilsson/) | 1998 | Neural networks, evolutionary algorithms, search, knowledge representation and reasoning, planning, Bayesian networks, etc. | Nilsson also wrote other important books related to AI and the philosophy of AI, such as [The Quest for Artificial Intelligence: A History of Ideas and Achievements](https://ai.stanford.edu/%7Enilsson/QAI/qai.pdf) (2009), among other important contributions to the AI field, such as [the robot *Shakey*](https://ai.stanford.edu/%7Enilsson/Shakey.mp4) and [*STRIPS*](https://apps.dtic.mil/sti/pdfs/ADA459687.pdf). |
  | [Artificial Intelligence: A Guide to Intelligent Systems](http://www.academia.dk/BiologiskAntropologi/Epidemiologi/DataMining/Artificial_Intelligence-A_Guide_to_Intelligent_Systems.pdf) | [Michael Negnevitsky](https://scholar.google.com/citations?user=XXsqjkgAAAAJ&hl=en) | 2005 (2nd edition) | Expert systems, fuzzy systems, artificial neural networks, evolutionary computation, hybrid systems, etc. |  |
  | [Artificial Intelligence: Structures and Strategies for Complex Problem Solving](http://www.uoitc.edu.iq/images/documents/informatics-institute/exam_materials/artificial%20intelligence%20structures%20and%20strategies%20for%20%20complex%20problem%20solving.pdf) | George Lugar | 2009 (6th edition) | History of AI, search, knowledge representation, expert systems, rule-based systems, machine learning, evolutionary algorithms, automated reasoning, natural language understanding, etc. | This book is mentioned by Ben Goertzel in his paper [Artificial General Intelligence: Concept, State of the Art, and Future Prospects](https://sciendo.com/article/10.2478/jagi-2014-0001) as a "popular AI textbook". |
  | [Artificial Intelligence: Foundations of Computational Agents](https://artint.info/2e/html/ArtInt2e.html) | David L. Poole, Alan K. Mackworth | 2017 (2nd edition) | Machine learning, search, planning, reasoning, and knowledge-based systems, etc. | I occasionally consulted this book. |
  
  
  ---
  
  ### Answer by username_3 on 2018-08-21. Score: 4
  
  The following 2 books helped me understand the basics and guided me through my first AI / CI implementations.
  
  * [**Computational Intelligence: An Introduction**](http://www.shahed.ac.ir/stabaii/Files/CompIntelligenceBook.pdf) by Andries P. Engelbrecht
  
    It includes the most relevant developments in computational intelligence with good discussions on intelligence and artificial intelligence (AI).
  * [**Computational Intelligence: Concepts to Implementation**](https://www.elsevier.com/books/computational-intelligence/eberhart/978-1-55860-759-0) by Russell C. Eberhart and Yuhui Shi
  
    It is a comprehensive textbook, supported with lots of practical examples.
  
  
  ---
  
  