# Decision Theory References and Resources ## Overview This document provides a comprehensive collection of online resources for learning about decision theory, including academic papers, tutorials, tools, and practical applications. ## Fundamental Concepts ### Decision Theory Basics - [Stanford Encyclopedia of Philosophy - Decision Theory](https://plato.stanford.edu/entries/decision-theory/) - [MIT OpenCourseWare - Decision Theory](https://ocw.mit.edu/courses/14-123-microeconomic-theory-iii-spring-2015/pages/lecture-notes/) - [Decision Theory: A Brief Introduction](https://people.kth.se/~soh/decisiontheory.pdf) - [Introduction to Decision Analysis](https://web.stanford.edu/class/cee115/wiki/uploads/Main/Schedule/CEE115_Lecture_2_IntroductionToDecisionAnalysis.pdf) ### Mathematical Foundations - [Probability Theory and Statistics](https://www.probabilitycourse.com/) - [Game Theory and Decision Theory](https://www.game-theory-class.org/) - [Utility Theory Fundamentals](https://www.econport.org/content/handbook/Utility.html) ## Decision Trees ### Tutorials and Guides - [Decision Tree Analysis - MindTools](https://www.mindtools.com/dectree.html) - [Harvard Business Review - A Refresher on Decision Trees](https://hbr.org/2014/04/a-refresher-on-decision-trees) - [Decision Trees for Decision Making](https://hbr.org/1964/07/decision-trees-for-decision-making) ### Software and Tools - [TreePlan - Excel Add-in for Decision Trees](https://treeplan.com/) - [SilverDecisions - Open Source Decision Tree Software](https://silverdecisions.pl/) - [Decision Tree Maker - Online Tool](https://www.lucidchart.com/pages/decision-tree-maker) ### Academic Resources - [Decision Trees in Machine Learning](https://www.cs.cmu.edu/~bhiksha/courses/10-601/decisiontrees/) - [ID3 Algorithm Paper by Quinlan](https://hunch.net/~coms-4771/quinlan.pdf) ## Markov Decision Processes (MDPs) ### Educational Resources - [Berkeley CS188 - MDPs](https://inst.eecs.berkeley.edu/~cs188/fa18/assets/slides/lec8.pdf) - [Stanford CS221 - Markov Decision Processes](https://stanford.edu/~shervine/teaching/cs-221/cheatsheet-markov-decision-processes) - [Reinforcement Learning: An Introduction (Sutton & Barto)](http://incompleteideas.net/book/the-book-2nd.html) ### Tutorials - [Towards Data Science - Introduction to MDPs](https://towardsdatascience.com/introduction-to-markov-decision-processes-6c1f9e2b4e8f) - [MDPs Tutorial with Python](https://www.analyticsvidhya.com/blog/2018/09/reinforcement-learning-model-based-planning-dynamic-programming/) ### Research Papers - [A Survey of Markov Decision Processes](https://www.cs.rice.edu/~vardi/dag01/givan1.pdf) - [Planning and Acting in Partially Observable Stochastic Domains](https://people.csail.mit.edu/lpk/papers/aij98-pomdp.pdf) ## Bayesian Networks ### Learning Resources - [Bayesian Networks Introduction - University of Wisconsin](https://pages.cs.wisc.edu/~dpage/cs760/BayesNets.pdf) - [Probabilistic Graphical Models Course - Stanford](https://www.coursera.org/learn/probabilistic-graphical-models) - [Introduction to Bayesian Networks](https://www.bayesserver.com/docs/introduction/bayesian-networks/) ### Tools and Software - [GeNIe - Graphical Network Interface](https://www.bayesfusion.com/genie/) - [Netica - Bayesian Network Software](https://www.norsys.com/) - [pgmpy - Python Library for Probabilistic Graphical Models](https://pgmpy.org/) ### Papers and Books - [Probabilistic Reasoning in Intelligent Systems (Pearl)](https://dl.acm.org/doi/book/10.5555/52121) - [Learning Bayesian Networks (Neapolitan)](https://www.cs.technion.ac.il/~dang/books/Learning%20Bayesian%20Networks(Neapolitan,%20Richard).pdf) ## Genetic Algorithms ### Introductory Material - [Introduction to Genetic Algorithms](https://www.geeksforgeeks.org/genetic-algorithms/) - [MIT Course - Genetic Algorithms](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/lecture-videos/lecture-13-learning-genetic-algorithms/) - [Genetic Algorithm Tutorial](https://www.tutorialspoint.com/genetic_algorithms/index.htm) ### Implementation Guides - [Building a Genetic Algorithm from Scratch](https://machinelearningmastery.com/simple-genetic-algorithm-from-scratch-in-python/) - [Genetic Algorithm Applications](https://www.sciencedirect.com/topics/engineering/genetic-algorithm-application) ### Research Resources - [Adaptation in Natural and Artificial Systems (Holland)](https://mitpress.mit.edu/books/adaptation-natural-and-artificial-systems) - [Genetic Algorithms in Search, Optimization, and Machine Learning](https://www.amazon.com/Genetic-Algorithms-Optimization-Machine-Learning/dp/0201157675) ## Multi-Criteria Decision Analysis (MCDA) ### Methods and Techniques - [Introduction to MCDA](https://www.mcdmsociety.org/content/introduction-mcdm) - [Analytic Hierarchy Process (AHP)](https://www.isahp.org/what-is-ahp) - [TOPSIS Method Explained](https://www.sciencedirect.com/topics/computer-science/technique-for-order-preference-by-similarity-to-ideal-solution) ### Software Tools - [Expert Choice - AHP Software](https://www.expertchoice.com/) - [1000minds - MCDA Tool](https://www.1000minds.com/) - [PROMETHEE Methods](http://www.promethee-gaia.net/methods.html) ## Online Courses and MOOCs ### Free Courses - [Coursera - Behavioral Economics and Decision Making](https://www.coursera.org/learn/behavioral-economics) - [edX - Decision Making in a Complex World](https://www.edx.org/course/decision-making-in-a-complex-and-uncertain-world) - [MIT OCW - Decision Making in Large Scale Systems](https://ocw.mit.edu/courses/aeronautics-and-astronautics/16-410-principles-of-autonomy-and-decision-making-fall-2010/) ### Specialized Programs - [Stanford Online - Decision Analysis](https://online.stanford.edu/courses/soe-ydecision-decision-analysis) - [Duke - Behavioral Finance](https://www.coursera.org/learn/duke-behavioral-finance) ## Books and Textbooks (Available Online) ### Classic Texts - [Decision Analysis for Management Judgment](https://www.wiley.com/en-us/Decision+Analysis+for+Management+Judgment%2C+5th+Edition-p-9781118740736) - [Smart Choices: A Practical Guide to Making Better Decisions](https://www.hbs.edu/faculty/Pages/item.aspx?num=10678) - [Thinking, Fast and Slow (Kahneman)](https://www.princeton.edu/~kahneman/) ### Technical Books - [The Foundations of Decision Analysis](https://www.pearson.com/us/higher-education/product/Howard-Foundations-of-Decision-Analysis/9780132336246.html) - [Decision Theory: Principles and Approaches](https://onlinelibrary.wiley.com/doi/book/10.1002/9780470746684) ## Software Libraries and APIs ### Python Libraries - [scikit-learn - Decision Trees](https://scikit-learn.org/stable/modules/tree.html) - [PyMC3 - Bayesian Statistical Modeling](https://docs.pymc.io/) - [DEAP - Distributed Evolutionary Algorithms](https://deap.readthedocs.io/) - [OR-Tools - Operations Research](https://developers.google.com/optimization) ### R Packages - [rpart - Recursive Partitioning](https://cran.r-project.org/web/packages/rpart/index.html) - [bnlearn - Bayesian Network Learning](https://www.bnlearn.com/) - [GA - Genetic Algorithms](https://cran.r-project.org/web/packages/GA/index.html) ### JavaScript Libraries - [decision-tree-js](https://github.com/lagodiuk/decision-tree-js) - [bayesian-network](https://github.com/bayesian-network/bayesian-network) - [genetic-js](https://github.com/subprotocol/genetic-js) ## Research Centers and Organizations ### Academic Institutions - [Stanford Decision and Risk Analysis](https://web.stanford.edu/dept/MSandE/cgi-bin/index.php) - [MIT Operations Research Center](https://orc.mit.edu/) - [Carnegie Mellon Decision Science](https://www.cmu.edu/dietrich/sds/) ### Professional Organizations - [Decision Analysis Society (INFORMS)](https://www.informs.org/Community/DAS) - [Society for Medical Decision Making](https://smdm.org/) - [International Society on MCDM](https://www.mcdmsociety.org/) ## Practical Applications ### Business and Management - [Harvard Business Review - Decision Making](https://hbr.org/topic/decision-making) - [McKinsey - Decision Making Insights](https://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/decision-making) - [MIT Sloan Review - Data & Analytics](https://sloanreview.mit.edu/tag/decision-making/) ### Healthcare - [Medical Decision Making Journal](https://journals.sagepub.com/home/mdm) - [Clinical Decision Support Systems](https://www.healthit.gov/topic/safety/clinical-decision-support) ### Public Policy - [RAND Corporation - Decision Support](https://www.rand.org/topics/decision-support.html) - [Policy Analysis and Decision Making](https://www.policylibrary.com/) ## Tools and Calculators ### Online Decision Tools - [Decision Matrix Calculator](https://www.mindtools.com/pages/article/newTED_03.htm) - [Expected Value Calculator](https://www.calculatorsoup.com/calculators/statistics/expected-value-calculator.php) - [Bayes' Theorem Calculator](https://www.statisticshowto.com/probability-and-statistics/bayes-theorem-problems/) ### Simulation Tools - [Monte Carlo Simulation](https://www.palisade.com/risk/) - [Crystal Ball - Oracle](https://www.oracle.com/applications/crystalball/) - [Arena Simulation Software](https://www.arenasimulation.com/) ## Forums and Communities ### Online Communities - [Reddit - r/DecisionTheory](https://www.reddit.com/r/DecisionTheory/) - [Stack Exchange - Operations Research](https://or.stackexchange.com/) - [Cross Validated - Statistics](https://stats.stackexchange.com/) ### Professional Networks - [LinkedIn - Decision Science Groups](https://www.linkedin.com/groups/) - [ResearchGate - Decision Theory](https://www.researchgate.net/topic/Decision-Theory) ## Blogs and Regular Content ### Academic Blogs - [Decision Science News](http://www.decisionsciencenews.com/) - [The Decision Lab](https://thedecisionlab.com/) - [Behavioral Economics Blog](https://behavioraleconomics.com/) ### Industry Blogs - [Towards Data Science - Decision Science](https://towardsdatascience.com/tagged/decision-science) - [Analytics Vidhya](https://www.analyticsvidhya.com/) - [KDnuggets - Decision Trees](https://www.kdnuggets.com/tag/decision-trees) ## Video Resources ### YouTube Channels - [3Blue1Brown - Probability](https://www.youtube.com/c/3blue1brown) - [StatQuest - Decision Trees](https://www.youtube.com/user/joshstarmer) - [Computerphile - AI Topics](https://www.youtube.com/user/Computerphile) ### Lecture Series - [MIT OpenCourseWare](https://www.youtube.com/user/MIT) - [Stanford Online](https://www.youtube.com/user/stanfordonline) - [Khan Academy - Statistics](https://www.khanacademy.org/math/statistics-probability) --- ## Contributing to Decision Theory If you're interested in contributing to the field of decision theory, consider: 1. **Publishing Research**: Submit to journals like Decision Analysis, Theory and Decision, or Management Science 2. **Open Source Projects**: Contribute to decision theory libraries on GitHub 3. **Teaching**: Create tutorials or educational content 4. **Industry Applications**: Implement decision theory methods in real-world problems --- *Last Updated: July 2025* *Note: All links were verified at the time of creation. Some links may become outdated over time. For the most current information, please search for the resource directly.*