Expose cut threshold when calculating CCE dist.

PiperOrigin-RevId: 377903873 Change-Id: I184688a45743081b3641874fa99ce4a218788b3e
amicodebase · Jun 13, 2021 · 56e7fe7 · 56e7fe7
1 parent 5c9e444
commit 56e7fe7
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Showing 3 changed files with 23 additions and 10 deletions.
diff --git a/open_spiel/algorithms/corr_dist.cc b/open_spiel/algorithms/corr_dist.cc
@@ -255,7 +255,8 @@ double CCEDist(const Game& game, const NormalFormCorrelationDevice& mu) {
 }
 
 CorrDistInfo CCEDist(
-    const Game& game, const CorrelationDevice& mu, int player) {
+    const Game& game, const CorrelationDevice& mu, int player,
+    const float prob_cut_threshold) {
   // Check for proper probability distribution.
   CheckCorrelationDeviceProbDist(mu);
   CorrDistConfig config;
@@ -273,7 +274,7 @@ CorrDistInfo CCEDist(
   CCETabularPolicy policy;
   std::unique_ptr<State> root = cce_game->NewInitialState();
   TabularBestResponse best_response(
-      *cce_game, player, &policy);
+      *cce_game, player, &policy, prob_cut_threshold);
   // Do not populate on policy values to save unnecessary computation.
   // dist_info.on_policy_values[0] = ExpectedReturns(
   //     *root, policy, -1, false)[player];
@@ -288,7 +289,9 @@ CorrDistInfo CCEDist(
   return dist_info;
 }
 
-CorrDistInfo CCEDist(const Game& game, const CorrelationDevice& mu) {
+CorrDistInfo CCEDist(
+    const Game& game, const CorrelationDevice& mu,
+    const float prob_cut_threshold) {
   // Check for proper probability distribution.
   CheckCorrelationDeviceProbDist(mu);
   CorrDistConfig config;
@@ -314,7 +317,8 @@ CorrDistInfo CCEDist(const Game& game, const CorrelationDevice& mu) {
 
   std::unique_ptr<State> root = cce_game->NewInitialState();
   for (auto p = Player{0}; p < cce_game->NumPlayers(); ++p) {
-    TabularBestResponse best_response(*cce_game, p, &policy);
+    TabularBestResponse best_response(
+        *cce_game, p, &policy, prob_cut_threshold);
     dist_info.best_response_values[p] = best_response.Value(*root);
     dist_info.best_response_policies[p] = best_response.GetBestResponsePolicy();
   }

diff --git a/open_spiel/algorithms/corr_dist.h b/open_spiel/algorithms/corr_dist.h
@@ -161,8 +161,10 @@ struct CorrDistInfo {
 // determines which policies the opponents follow (never revealed). Note that
 // the policies in this correlation device *can* be mixed. If values is
 // non-null, then it is filled with the deviation incentive of each player.
-CorrDistInfo CCEDist(const Game& game, const CorrelationDevice& mu);
-CorrDistInfo CCEDist(const Game& game, const CorrelationDevice& mu, int player);
+CorrDistInfo CCEDist(const Game& game, const CorrelationDevice& mu,
+                     const float prob_cut_threshold = -1.0);
+CorrDistInfo CCEDist(const Game& game, const CorrelationDevice& mu, int player,
+                     const float prob_cut_threshold = -1.0);
 
 // Distance to a correlated equilibrium in an extensive-form game. Builds a
 // simpler auxiliary game similar to the *FCE ones where there is a chance node

diff --git a/open_spiel/python/pybind11/algorithms_corr_dist.cc b/open_spiel/python/pybind11/algorithms_corr_dist.cc
@@ -51,14 +51,21 @@ void init_pyspiel_algorithms_corr_dist(py::module& m) {
                     &CorrDistInfo::conditional_best_response_policies);
 
   m.def("cce_dist",
-        py::overload_cast<const Game&, const CorrelationDevice&, int>(
+        py::overload_cast<const Game&, const CorrelationDevice&, int, float>(
             &open_spiel::algorithms::CCEDist),
-        "Returns a player's distance to a coarse-correlated equilibrium.");
+        "Returns a player's distance to a coarse-correlated equilibrium.",
+        py::arg("game"),
+        py::arg("correlation_device"),
+        py::arg("player"),
+        py::arg("prob_cut_threshold") = -1.0);
 
   m.def("cce_dist",
-        py::overload_cast<const Game&, const CorrelationDevice&>(
+        py::overload_cast<const Game&, const CorrelationDevice&, float>(
             &open_spiel::algorithms::CCEDist),
-        "Returns the distance to a coarse-correlated equilibrium.");
+        "Returns the distance to a coarse-correlated equilibrium.",
+        py::arg("game"),
+        py::arg("correlation_device"),
+        py::arg("prob_cut_threshold") = -1.0);
 
   m.def("ce_dist",
         py::overload_cast<const Game&, const CorrelationDevice&>(