QuantEcon / GameTheory.jl

Algorithms and data structures for game theory in Julia
Other
123 stars 24 forks source link

Review notes on learning algorithms #127

Closed Yuya-Furusawa closed 4 years ago

Yuya-Furusawa commented 4 years ago

@oyamad Please review the notes on learning algorithms(PR) Fictitious Play Local Interaction Best Response Dynamics Logit Response Dynamics

MKobayashi23m commented 4 years ago

I reviewed the notes. First, let me make some comments on Fictitious Play.

In the first line, in the cell below the one with notations for strategy sets and others, “After each round of play, players observe the actual actions choosen by opponents, ...“

In the cell next to the definition of the wight function, “Each player assesses concerning the behavior of his opponents at each date and contingent on history”

In the next cell,

In the cell that mentions the condition of the convergence of fictions play,

On the explanation of play, The explanation says the play method “returns the new normalized actions history …” but it seems not. The displayed output looks like a mixed strategy profile and not a history.

“If you don't designate initial actions, they are choosed randomly.”

On the explanation of time_series,

On the explanation of the graph of the two-action simulation, “… This result is consistent with manu papers.”

On the explanation of the graph of the three-action-game simulation, “… correspond to player's belief for opponent's first, second third action respectively”

In the description of the Model of Stochastic Fictitious Play, “Almost all of the settings are same as original fictitious play model except for paerturbated payoff.” → “Almost all of the settings are the same as original fictitious play model except for perturbed payoff.” ?

“Note that we do not need to consider mixed startegies in this augmented game.”

“…(i) two-player symmetric game with an interior ESS…”

On “Stochastic Fictitious Play with constant gain” part,

MKobayashi23m commented 4 years ago

Please ignore unnecessary comments. I'm going to upload comment for the rest ASAP.

Yuya-Furusawa commented 4 years ago

@MKobayashi23m Thank you for the polite check!

We created another repository for the game theory notebooks. https://github.com/QuantEcon/game-theory-notebooks I'm sorry I forgot to contact you about this, and let's discuss here.

(I will close this issue after you check this comment)

MKobayashi23m commented 4 years ago

@Yuya-Furusawa

Understood! Thank you. I will join in the repository.