using Pkg; Pkg.add("CounterfactualRegret")| Solver Name | Description |
|---|---|
CFRSolver |
Vanilla CFR solver |
CSCFRSolver |
Chance Sampling |
ESCFRSolver |
External Sampling |
OSCFRSolver |
Outcome Sampling |
Each solver takes optional kwarg method, which can be an instantiation of either Vanilla, Plus, or Discount types, which correspond to Vanilla CFR, CFR+, and discounted CFR respectively.
| Name | Status |
|---|---|
| DeepCFR |   |
| ESCHER |   |
| POMDPBestResponse |   |
using CounterfactualRegret
const CFR = CounterfactualRegret
using CounterfactualRegret.Games
using Plots
game = MatrixGame([
(1,1) (0,0) (0,0);
(0,0) (0,2) (3,0);
(0,0) (2,0) (0,3);
])
sol = CFRSolver(game; debug=true)
cb = CFR.ExploitabilityCallback(sol, 10) # optional callback to monitor training
train!(sol, 10_000; cb=cb)
plot(cb, lw=2)
Kuhn Poker Implementation & Game Definition Tutorial
game = Kuhn()
sol = ESCFRSolver(game; method=Discount(α=1.0, β=1.0, γ=1.0))
cb = CFR.ExploitabilityCallback(sol)
train!(sol, 100_001; cb=cb)
hist = cb.hist
exp_idxs = 10 .^(0:5) .+ 1
plot(
hist.x[exp_idxs], hist.y[exp_idxs];
xscale = :log10, lw=2, label="",
xlabel = "Training Iterations",
ylabel = "Exploitability"
)