Master in Game Theory
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Want to become a Master in Game Theory but don’t know what to do and how?
Take a look at this course where you will
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Not only learn about the Game Theory in depth interactively with a lot of examples including Modeling the Game, Classifying the Game, Analyzing Strategic Interactions, Solving the Game, Considering Repeated Games, Considering Stochastic Games, Applying Equilibrium Concepts, and Contextual Analysis but also
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Open doors to a variety of careers across different fields
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Preview many lectures for free to see the content for yourself
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Clear your doubts on this topic any time while doing the course
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Get Udemy’s 30 days Money Back Guarantee
My first exposure to Game Theory happened very early in life in my childhood when I started playing Chess which taught me to think a few moves ahead of your opponent and decide your own move to ultimately win the game. Looking back, I learnt about considering all the probable move my opponent would make and then decide my own move to pre-empt the opponent
Formally introduction to Game Theory happened in 1979-81 when doing my MBA at Indian Institute of Management, Bangalore where I learnt how to apply these concepts in making right decision in management
The journey to learn practically more about Game Theory continued over my working life since 1981 till 2016 when I refreshed my learning about Game Theory to teach and coach the MBA students at Indian Institute of Management, Udaipur.
I bring in this course my learnings from this journey and share with you how can you also Master Game Theory
Preview for yourself many lectures free. If you like the content, enrol for the course, enjoy and skill yourself to become a Master in Game Theory! If don’t like the content, please message about how can we modify it to meet your expectations.
Please remember that this course comes with Udemy’s 30 days Money Back Guarantee
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Overview IAt the end of this section, you will learn the following
•What is Game Theory
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Overview IPlease answer following questions based on learnings in this lecture
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Overview II
At the end of this section, you will learn the following
•What careers can you take after learning Game Theory
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Overview II
Please answer following questions based on learnings in this lecture
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Overview III
At the end of this section, you will learn the following
•Game Theory Framework
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Overview III
Please answer following questions based on learnings in this lecture
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Overview IV
At the end of this section, you will learn the following
•An example of Game Theory application
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Modeling The Game I
At the end of this course, you will learn the following
•Identifying Players: Determine who the decision-makers are in the scenario
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Modeling The Game I
Please answer following questions based on learnings in this lecture
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Modeling The Game II
At the end of this course, you will learn the following
•Defining Strategies: List all possible actions or strategies each player can take
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Modeling The Game II
Please answer following questions based on learnings in this lecture
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Modeling The Game III
At the end of this course, you will learn the following
•Specifying Payoffs: Quantify the rewards or outcomes for each combination of strategies chosen by the players
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Modeling The Game III
Please answer following questions based on learnings in this lecture
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Modeling The Game IV
At the end of this course, you will learn the following
An example of Modeling The Game
•Identification the Decision-Maker
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Modeling The Game V
At the end of this course, you will learn the following
An example of Modeling The Game
•Strategies Identification
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Modeling The Game VI
At the end of this course, you will learn the following
An example of Modeling The Game
•Quantifying Payoffs
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Classifying The Game I
At the end of this lecture, you will learn the following
•How to determine whether the game is cooperative or non-cooperative, symmetric or asymmetric, zero-sum or non-zero-sum, and simultaneous or sequential
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Classifying The Game I
Please answer following questions based on learnings in this lecture
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Classifying The Game II
At the end of this lecture, you will learn the following
•An example of determining whether the game is cooperative or non-cooperative, symmetric or asymmetric, zero-sum or non-zero-sum, and simultaneous or sequential
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Classifying The Game III
At the end of this course, you will learn the following
•How to choose between normal (strategic) form and extensive form. The normal form uses matrices to represent payoffs, while the extensive form uses game trees to show sequential decisions
•An example of choosing between normal (strategic) form and extensive form. The normal form uses matrices to represent payoffs, while the extensive form uses game trees to show sequential decisions
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Classifying The Game III
Please answer following questions based on learnings in this lecture
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23
Analyzing Strategic Interactions I
At the end of this lecture, you will learn the following
•How to identify if any player has a dominant strategy, which is the best action regardless of what others do
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Analyzing Strategic Interactions I
Please answer following questions based on learnings in this lecture
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Analyzing Strategic Interactions II
At the end of this lecture, you will learn the following
•How to find the set of strategies where no player can benefit by changing their strategy unilaterally. This represents a stable state where players' strategies are mutual best responses
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Analyzing Strategic Interactions II
Please answer following questions based on learnings in this lecture
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Analyzing Strategic Interactions III
At the end of this lecture, you will learn the following
•For games without pure strategy equilibria, how to consider mixed strategies where players randomize over possible actions
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Analyzing Strategic Interactions III
Please answer following questions based on learnings in this lecture
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Solving The Game I
At the end of this lecture, you will learn the following
•In sequential games, how to use backward induction to determine optimal strategies by analyzing the game from the end to the beginning
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Solving The Game I
Please answer following questions based on learnings in this lecture
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Solving The Game II
At the end of this lecture, you will learn the following
•In some games, how to iteratively eliminate dominated strategies (strategies that are always worse than another strategy) to simplify the analysis
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Solving The Game II
Please answer following questions based on learnings in this lecture
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Considering Repeated Games I
At the end of this lecture, you will learn the following
How to analyze strategies in games that are played multiple times, considering the impact of past actions on future decisions and outcomes
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Considering Repeated Games I
Please answer following questions based on learnings in this lecture
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Considering Repeated Games II
At the end of this lecture, you will learn the following
How to analyze strategies in games that are played multiple times, considering the impact of past actions on future decisions and outcomes
Analyze Equilibria
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Considering Repeated Games II
Please answer following questions based on learnings in this lecture
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Considering Repeated Games III
At the end of this lecture, you will learn the following
How to analyze strategies in games that are played multiple times, considering the impact of past actions on future decisions and outcomes
Analyze Equilibria
How to ensure the strategy is an equilibrium in every subgame of the repeated
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Considering Repeated Games III
Please answer following questions based on learnings in this lecture
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Considering Repeated Games IV
At the end of this lecture, you will learn the following
How to analyze strategies in games that are played multiple times, considering the impact of past actions on future decisions and outcomes
How to Use Folk Theorem
Key Concepts
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Considering Repeated Games IV
Please answer following questions based on learnings in this lecture
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Considering Repeated Games V
At the end of this lecture, you will learn the following
How to analyze strategies in games that are played multiple times, considering the impact of past actions on future decisions and outcomes
•How to Use Folk Theorem
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Considering Repeated Games V
Please answer following questions based on learnings in this lecture
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Considering Repeated Games VI
At the end of this lecture, you will learn the following
How to analyze strategies in games that are played multiple times, considering the impact of past actions on future decisions and outcomes
How to Consider History-Dependent Strategies
Evaluate how past actions influence current decisions
Understanding History-Dependent Strategies
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Considering Repeated Games VI
Please answer following questions based on learnings in this lecture
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Considering Repeated Games VII
At the end of this lecture, you will learn the following
How to analyze strategies in games that are played multiple times, considering the impact of past actions on future decisions and outcomes
How to Consider History-Dependent Strategies
How to evaluate how past actions influence current decisions
Setting Up the Framework
Analyzing the Impact of History on Current Decisions
Evaluating Specific Strategies
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Considering Repeated Games VII
Please answer following questions based on learnings in this lecture
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Considering Repeated Games VIII
At the end of this lecture, you will learn the following
How to analyze strategies in games that are played multiple times, considering the impact of past actions on future decisions and outcomes
•How to Consider History-Dependent Strategies
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Considering Repeated Games VIII
Please answer following questions based on learnings in this lecture
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Considering Repeated Games IX
At the end of this lecture, you will learn the following
How to analyze strategies in games that are played multiple times, considering the impact of past actions on future decisions and outcomes
How to Consider History-Dependent Strategies
Detailed Evaluation of Common Strategies- Grim Trigger
Detailed Evaluation of Common Strategies- Pavlov Strategy
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Considering Repeated Games IX
Please answer following questions based on learnings in this lecture
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Considering Repeated Games X
At the end of this lecture, you will learn the following
How to analyze strategies in games that are played multiple times, considering the impact of past actions on future decisions and outcomes
•How to Consider History-Dependent Strategies
Formal Analysis Using Mathematical Tools
How to use dynamic programming to evaluate the value function
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Considering Repeated Games X
Please answer following questions based on learnings in this lecture
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Considering Repeated Games XI
At the end of this lecture, you will learn the following
How to analyze strategies in games that are played multiple times, considering the impact of past actions on future decisions and outcomes
•How to Consider History-Dependent Strategies
Formal Analysis Using Mathematical Tools
How to use dynamic programming to evaluate the value function
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Considering Repeated Games XI
Please answer the following questions based on learnings in this lecture
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Considering Repeated Games XII
At the end of this lecture, you will learn the following
How to analyze strategies in games that are played multiple times, considering the impact of past actions on future decisions and outcomes
•How to Consider History-Dependent Strategies
Formal Analysis Using Mathematical Tools
How to use dynamic programming to evaluate the value function- An Example
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Considering Repeated Games XII
Please answer following questions based on learnings in this lecture
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Considering Repeated Games XIII
At the end of this lecture, you will learn the following
How to analyze strategies in games that are played multiple times, considering the impact of past actions on future decisions and outcomes
•How to Consider History-Dependent Strategies
How to evaluate how past actions influence current decisions
Evaluating Through Simulation
Monte Carlo Simulations
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Considering Repeated Games XIII
Please answer following questions based on learnings in this lecture
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Considering Repeated Games XIV
At the end of this lecture, you will learn the following
How to analyze strategies in games that are played multiple times, considering the impact of past actions on future decisions and outcomes
•How to Consider History-Dependent Strategies
How to evaluate how past actions influence current decisions
Evaluating Through Simulation
Statistical Analysis
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Considering Repeated Games XIV
Please answer following questions based on learnings in this lecture
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Considering Repeated Games XV
At the end of this lecture, you will learn the following
How to analyze strategies in games that are played multiple times, considering the impact of past actions on future decisions and outcomes
•How to Consider History-Dependent Strategies
Use the history of play to determine future strategies
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Considering Repeated Games XV
Please answer following questions based on learnings in this lecture
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Considering Stochastic Games I
At the end of this lecture, you will learn the following
•How to account for random events and probabilistic transitions between states in dynamic strategic interactions
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Considering Stochastic Games I
Please answer following questions based on learnings in this lecture
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Considering Stochastic Games II
At the end of this lecture, you will learn the following
•How to account for random events and probabilistic transitions between states in dynamic strategic interactions
Solving MDP
Value Iteration
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Considering Stochastic Games II
Please answer following questions based on learnings in this lecture
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Considering Stochastic Games III
At the end of this lecture, you will learn the following
How to account for random events and probabilistic transitions between states in dynamic strategic interactions
Solving MDP
An example of Value Iteration
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Considering Stochastic Games IV
At the end of this lecture, you will learn the following
How to account for random events and probabilistic transitions between states in dynamic strategic interactions
Solving MDP
Policy Iteration
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Considering Stochastic Games IV
Please answer following questions based on learnings in this lecture
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Considering Stochastic Games V
At the end of this lecture, you will learn the following
•How to account for random events and probabilistic transitions between states in dynamic strategic interactions
Solving MDP
Policy Iteration Example
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Considering Stochastic Games VI
At the end of this lecture, you will learn the following
How to account for random events and probabilistic transitions between states in dynamic strategic interactions
Stochastic Games
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Considering Stochastic Games VI
Please answer following questions based on learnings in this lecture
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Considering Stochastic Games VII
At the end of this lecture, you will learn the following
How to account for random events and probabilistic transitions between states in dynamic strategic interactions
Stochastic Games Example
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Applying Equilibrium Concepts I
At the end of this lecture, you will learn the following
•Evaluating if the outcomes are Pareto efficient, meaning no player can be made better off without making another player worse off.
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Applying Equilibrium Concepts I
Please answer following questions based on learnings in this lecture
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Applying Equilibrium Concepts II
At the end of this lecture, you will learn the following
Evaluating if the outcomes are Pareto efficient, meaning no player can be made better off without making another player worse off
•How to make graphical representation of Pareto efficient outcomes
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Applying Equilibrium Concepts II
Please answer following questions based on learnings in this lecture
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Applying Equilibrium Concepts III
At the end of this lecture, you will learn the following
How to, in extensive form games, ensure that strategies constitute a Nash equilibrium in every subgame?
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Applying Equilibrium Concepts III
Please answer following questions based on learnings in this lecture
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Applying Equilibrium Concepts IV
At the end of this lecture, you will learn the following
For games with incomplete information where players have beliefs about unknown factors, how to use Bayesian Nash equilibrium to incorporate probabilistic reasoning?
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Applying Equilibrium Concepts IV
Please answer following questions based on learnings in this lecture
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Applying Equilibrium Concepts V
At the end of this lecture, you will learn the following
Example of Bayesian Nash Equilibrium
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Applying Equilibrium Concepts V
Please answer following questions based on learnings in this lecture
