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Thomas Woolf
This is part of our specialization on Making Decision in Time. For this third course we start with an intriguing study on SFPark and build new insights into the ideas that flow from this direction. The ending point should bring new code and new algorithm insights into perspective, and use, by many computer and data scientists.
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What's inside
Syllabus
Dynamically Changing Environments and Game Theory
How should a control be adjusted to best achieve a desired outcome? We introduce the SFPark problem, a real parking management approach being used in SF. The question that we want to understand, via sequential methods and games, is how best to set the prices for spaces, dynamically during the day, to encourage a particular (say 15%) free space availability. The game is between the consumers (looking for parking) and the city (trying to optimize space, reducing those cruising for spaces and encouraging those coming for a meal or for shopping to have a parking space). This is a sequential decision problem that can also be described as a game.
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Syllabus
Dynamically Changing Environments and Game Theory
How should a control be adjusted to best achieve a desired outcome? We introduce the SFPark problem, a real parking management approach being used in SF. The question that we want to understand, via sequential methods and games, is how best to set the prices for spaces, dynamically during the day, to encourage a particular (say 15%) free space availability. The game is between the consumers (looking for parking) and the city (trying to optimize space, reducing those cruising for spaces and encouraging those coming for a meal or for shopping to have a parking space). This is a sequential decision problem that can also be described as a game.
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Designed for students with an interest in computational social science
Guides learners in understanding how to make decisions in dynamic environments
Taught by Thomas Woolf, a recognized expert in decision-making theory
Examines real-world applications of game theory, including the SFPark parking management system
Covers advanced topics such as sequential social environments and avoiding distribution shifts
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Reviews summary
Theoretical depth in data science decisions
Learners say this course offers a deep dive into decision-making in data science, particularly focusing on information theory and game theory concepts. Many commend the instructor's profound knowledge and the challenging yet rewarding nature of the material, finding it excellent for those with a solid quantitative background. However, some indicate it is highly demanding and not suitable for beginners, with dense lectures and complex assignments that may require significant self-study to grasp fully.
Strong theoretical base, but some sought more hands-on coding or practical examples.
"The theory is solid, which is great, but I was hoping for more practical coding exercises to apply what I learned."
"I gained a deep theoretical understanding, which is what I wanted, but others might need more direct code demonstrations."
"While the SFPark case study was insightful, I wished for more diverse real-world implementations beyond the conceptual."
Instructor demonstrates deep expertise and passion for the subject.
"The professor clearly understands the material inside and out, making the lectures insightful and engaging."
"I found the instructor's explanations, while sometimes fast, to be very profound and thought-provoking."
"His experience in the field shone through, providing valuable context and real-world relevance to the theories."
Provides a rigorous, in-depth exploration of complex concepts.
"The course delves into advanced topics with mathematical rigor, offering a truly comprehensive understanding."
"I appreciated the comprehensive coverage of game theory applied to real-world problems and data science scenarios."
"It offers a strong conceptual foundation, moving beyond surface-level explanations into the core principles."
Assignments are complex and require significant independent problem-solving.
"The assignments were incredibly difficult, sometimes feeling disconnected from the lectures and requiring extensive self-study."
"I spent hours trying to decipher what was expected in some homework problems; more examples would have been helpful."
"While challenging, the problems really pushed my understanding, but I wished for more step-by-step guidance on harder tasks."
Highly challenging; best for learners with prior math/CS experience.
"This course is not for the faint of heart; I felt lost without a solid math and programming background."
"Prior knowledge in probability, linear algebra, and even some basic optimization is absolutely essential to keep up."
"If you are a beginner in data science or game theory, prepare for a steep learning curve and a lot of extra effort."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Data Science Decisions in Time: Information Theory & Games with these
activities:
Review key concepts in game theory
Show steps
Brushing up on fundamental concepts will help you understand the more advanced topics covered in this course.
Show steps
-
Go over your lecture notes or textbook chapters on game theory.
-
Review online resources or articles to reinforce your understanding.
-
Solve practice problems to test your knowledge.
Compile a collection of resources on game theory and its applications
Show steps
Creating a compilation will provide you with a valuable reference and help you stay organized.
Browse courses on
Online Courses
Show steps
-
Identify different types of resources (e.g., books, articles, videos).
-
Search for and gather relevant resources.
-
Organize and categorize the resources.
-
Consider creating an online repository or sharing your compilation with others.
Attend conferences or meetups focused on game theory or artificial intelligence
Show steps
Attending events will allow you to connect with professionals in the field, learn about current research, and stay up-to-date with industry trends.
Browse courses on
Networking
Show steps
-
Identify relevant conferences or meetups in your area.
-
Register and attend the events.
-
Engage with speakers, attendees, and exhibitors.
-
Follow up with interesting contacts.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice solving game theory problems
Show steps
Regular practice will strengthen your problem-solving skills and improve your ability to apply game theory concepts.
Browse courses on
Dynamic programming
Show steps
-
Find practice problems online or in textbooks.
-
Start with easier problems and gradually increase the difficulty.
-
Review your solutions and identify areas for improvement.
Explore online tutorials on advanced game theory topics
Show steps
Following guided tutorials will introduce you to new concepts and techniques that can extend your knowledge.
Browse courses on
Mechanism Design
Show steps
-
Identify specific topics or areas where you want to expand your knowledge.
-
Search for reputable online tutorials or courses on those topics.
-
Follow the tutorials and complete the exercises or assignments.
Develop a case study on a real-world application of game theory
Show steps
Creating a case study will deepen your understanding of game theory and its practical implications.
Browse courses on
Real-World Examples
Show steps
-
Choose a specific real-world scenario that involves game theory.
-
Research and gather data on the scenario.
-
Analyze the scenario using game theory principles.
-
Develop recommendations based on your analysis.
-
Write up your case study and share it with others.
Contribute to open-source projects related to game theory or artificial intelligence
Show steps
Contributing to open-source projects will provide you with hands-on experience and deepen your understanding of the latest advancements.
Browse courses on
AI Algorithms
Show steps
-
Find open-source projects that align with your interests and skill level.
-
Review the project documentation and identify areas where you can contribute.
-
Make code contributions, bug fixes, or documentation improvements.
-
Engage with the project community and learn from others.
Review key concepts in game theory
Show steps
Brushing up on fundamental concepts will help you understand the more advanced topics covered in this course.
Show steps
Show steps
Show steps
- Go over your lecture notes or textbook chapters on game theory.
- Review online resources or articles to reinforce your understanding.
- Solve practice problems to test your knowledge.
Compile a collection of resources on game theory and its applications
Show steps
Creating a compilation will provide you with a valuable reference and help you stay organized.
Browse courses on
Online Courses
Show steps
Show steps
Show steps
- Identify different types of resources (e.g., books, articles, videos).
- Search for and gather relevant resources.
- Organize and categorize the resources.
- Consider creating an online repository or sharing your compilation with others.
Attend conferences or meetups focused on game theory or artificial intelligence
Show steps
Attending events will allow you to connect with professionals in the field, learn about current research, and stay up-to-date with industry trends.
Browse courses on
Networking
Show steps
Show steps
Show steps
- Identify relevant conferences or meetups in your area.
- Register and attend the events.
- Engage with speakers, attendees, and exhibitors.
- Follow up with interesting contacts.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice solving game theory problems
Show steps
Regular practice will strengthen your problem-solving skills and improve your ability to apply game theory concepts.
Browse courses on
Dynamic programming
Show steps
Show steps
Show steps
- Find practice problems online or in textbooks.
- Start with easier problems and gradually increase the difficulty.
- Review your solutions and identify areas for improvement.
Explore online tutorials on advanced game theory topics
Show steps
Following guided tutorials will introduce you to new concepts and techniques that can extend your knowledge.
Browse courses on
Mechanism Design
Show steps
Show steps
Show steps
- Identify specific topics or areas where you want to expand your knowledge.
- Search for reputable online tutorials or courses on those topics.
- Follow the tutorials and complete the exercises or assignments.
Develop a case study on a real-world application of game theory
Show steps
Creating a case study will deepen your understanding of game theory and its practical implications.
Browse courses on
Real-World Examples
Show steps
Show steps
Show steps
- Choose a specific real-world scenario that involves game theory.
- Research and gather data on the scenario.
- Analyze the scenario using game theory principles.
- Develop recommendations based on your analysis.
- Write up your case study and share it with others.
Contribute to open-source projects related to game theory or artificial intelligence
Show steps
Contributing to open-source projects will provide you with hands-on experience and deepen your understanding of the latest advancements.
Browse courses on
AI Algorithms
Show steps
Show steps
Show steps
- Find open-source projects that align with your interests and skill level.
- Review the project documentation and identify areas where you can contribute.
- Make code contributions, bug fixes, or documentation improvements.
- Engage with the project community and learn from others.
Career center
Learners who complete Data Science Decisions in Time: Information Theory & Games will develop knowledge and skills
that may be useful to these careers:
For more career information including salaries, visit:
OpenCourser.com/course/f9q3vd/data
Reading list
We haven't picked any books for this reading list yet.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/f9q3vd/data
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