How to Solve Bayesian Game Equations?

In summary, the conversation discusses the example problem of Cournot Duopoly with incomplete information, where firm 1 has one known type and firm 2 has private information about its type. The profit functions and decision problems for both firms are given, and the steps to solve for the pure strategy equilibrium are explained. This involves deriving best response functions for both firms and using probabilities to compute the Nash equilibrium. The final solutions for the quantities produced by each firm are obtained through solving a system of equations.
  • #1
Poisonous
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Homework Statement



My Textbook gives the following example problem:

Cournot Duopoly with incomplete information.

The profit functions are given by:
u_i = q_i(θ_¡ - q_i - q_j)

Firm 1 has one type θ_1 = 1, but firm 2 has private information about its type θ_2. Firm 1
believes that θ_2= 3/4 with probability 1/2 and θ _2 = 5/4 with probability 1/2, and this belief is common knowledge.

We will look for a pure strategy equilibrium of this game. Firm 2 of type θ_2’s decision
problem is to

max q_2: q_2(θ_2 - q_1 - q_2)

which is solved at
q_'2(θ_2) = (θ_2-q_1)/2


Firm 1’s decision problem, on the other hand, is
max q_1: 1/2 * q_1 (1 - q_1 - q_'2(3/4)) + 1/2 * q_1(1-q_1-q_'2(5/4))

which is solved at
q_'1 = (2-q_'2 (3/4)-q_'2(5/4))/4

Solving yields,
q_'1 = 1/3
q_'2(3/4) = 11/24
q_'2(5/4) = 5/24

Atempt at a solution

I can't figure out how they got from the equations q_'1 and q_'2 to the answers given in the "solving yields" part. It seems like simultaneous equations, but I'm not sure what to do with the q_1 or really where to begin.
 
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  • #2
Recall that in any bayesian game, strategies are mappings from types to quantities. This means that firm 2 'quantity' must specify what the the type [itex]\theta_{2}=3/4[/itex] will produce and how much the type [itex]\theta_{2}=5/4[/itex] will produce. Now, since firm 2 knows his own type, it can maximize using this information: this is why you obtain two best response functions, one for each type. Next, to compute the Nash equilibrium you also need to derive a best response for firm 1. Firm 1 only know the probability of each type and hence, incorporates two different quantities (one for each type) together with the probabilities of meeting each type in his maximization problem. This will give you a third best response that must be a function of the quantity type [itex]\theta_2=3/4[/itex] is expected to produce, and the quantity that type [itex]\theta_2=5/4[/itex] is expected to produce. All this gives you 3 equations (2 best responses for firm 2 and one for firm 1) and 3 unknowns (quanties for each type of firm 2 and the quantity for firm 1). You can solve this system of equations the way you like (substitution, reduction, etc). This will give you the solutions you state in the last part of your question.
 

Related to How to Solve Bayesian Game Equations?

1. What is game theory?

Game theory is a branch of mathematics and economics that studies decision-making in situations where two or more players have conflicting interests. It provides a framework for analyzing strategic interactions between rational individuals or organizations.

2. How is game theory used?

Game theory is used in a variety of fields, including economics, political science, psychology, and biology. It can be used to model and analyze various situations, such as negotiations, auctions, and competition between businesses.

3. What are the key concepts in game theory?

Some key concepts in game theory include players, strategies, payoffs, and equilibrium. Players are the individuals or organizations involved in the game, strategies are the actions they can take, payoffs are the outcomes of the game, and equilibrium is the optimal outcome for all players.

4. Can game theory predict human behavior?

While game theory can provide insights into decision-making and strategic interactions, it cannot predict the behavior of individual players with 100% accuracy. Human behavior can be influenced by various factors, such as emotions and personal values, which are difficult to model using game theory.

5. What are some limitations of game theory?

One limitation of game theory is that it assumes all players are rational and have perfect information, which may not always be the case in real-world situations. It also does not consider the possibility of cooperation between players, as it primarily focuses on competitive interactions. Additionally, game theory can become complex and difficult to apply in situations with multiple players and strategies.

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