ENH: Add is_absent_minded property to Infoset

ChangeLog

@@ -2,6 +2,10 @@
 
 ## [16.5.0] - unreleased
 
+### Added
+- Implement `IsAbsentMinded()` on information sets (C++) and `Infoset.is_absent_minded` (Python)
+  to detect if an information is absent-minded.
+
 ### Changed
 - In the graphical interface, removed option to configure information set link drawing; information sets
   are always drawn and indicators are always drawn if an information set spans multiple levels.

doc/pygambit.api.rst

@@ -158,6 +158,7 @@ Information about the game
    Infoset.label
    Infoset.game
    Infoset.is_chance
+   Infoset.is_absent_minded
    Infoset.player
    Infoset.actions
    Infoset.members

src/games/game.h

@@ -759,6 +759,14 @@ class GameRep : public std::enable_shared_from_this<GameRep> {
 
   /// Returns true if the game is perfect recall
   virtual bool IsPerfectRecall() const = 0;
+  /// Returns true if the information set is absent-minded
+  virtual bool IsAbsentMinded(const GameInfoset &p_infoset) const
+  {
+    if (p_infoset->GetGame().get() != this) {
+      throw MismatchException();
+    }
+    return false;
+  }
   //@}
 
   /// @name Writing data files

src/games/gametree.cc

@@ -819,6 +819,19 @@ bool GameTreeRep::IsPerfectRecall() const
                      [](const auto &pair) { return pair.second.size() <= 1; });
 }
 
+bool GameTreeRep::IsAbsentMinded(const GameInfoset &p_infoset) const
+{
+  if (p_infoset->GetGame().get() != this) {
+    throw MismatchException();
+  }
+
+  if (!m_unreachableNodes && !m_root->IsTerminal()) {
+    BuildUnreachableNodes();
+  }
+
+  return contains(m_absentMindedInfosets, p_infoset.get());
+}
+
 //------------------------------------------------------------------------
 //               GameTreeRep: Managing the representation
 //------------------------------------------------------------------------
@@ -870,6 +883,7 @@ void GameTreeRep::ClearComputedValues() const
   const_cast<GameTreeRep *>(this)->m_nodePlays.clear();
   m_ownPriorActionInfo = nullptr;
   const_cast<GameTreeRep *>(this)->m_unreachableNodes = nullptr;
+  m_absentMindedInfosets.clear();
   m_computedValues = false;
 }
 
@@ -1008,7 +1022,7 @@ std::set<GameAction> GameTreeRep::GetOwnPriorActions(const GameInfoset &p_infose
   return result;
 }
 
-void GameTreeRep::BuildUnreachableNodes()
+void GameTreeRep::BuildUnreachableNodes() const
 {
   m_unreachableNodes = std::make_unique<std::set<GameNodeRep *>>();
 
@@ -1052,6 +1066,7 @@ void GameTreeRep::BuildUnreachableNodes()
     if (!child->IsTerminal()) {
       // Check for Absent-Minded Re-entry of the infoset
       if (path_choices.find(child->m_infoset->shared_from_this()) != path_choices.end()) {
+        m_absentMindedInfosets.insert(child->m_infoset);
         const GameAction replay_action = path_choices.at(child->m_infoset->shared_from_this());
         position.emplace(AbsentMindedEdge{replay_action, child});
 

src/games/gametree.h

@@ -47,6 +47,7 @@ class GameTreeRep : public GameExplicitRep {
   std::map<GameNodeRep *, std::vector<GameNodeRep *>> m_nodePlays;
   mutable std::shared_ptr<OwnPriorActionInfo> m_ownPriorActionInfo;
   mutable std::unique_ptr<std::set<GameNodeRep *>> m_unreachableNodes;
+  mutable std::set<GameInfosetRep *> m_absentMindedInfosets;
 
   /// @name Private auxiliary functions
   //@{
@@ -86,6 +87,7 @@ class GameTreeRep : public GameExplicitRep {
   Rational GetPlayerMinPayoff(const GamePlayer &) const override;
   /// Returns the largest payoff to the player in any play of the game
   Rational GetPlayerMaxPayoff(const GamePlayer &) const override;
+  bool IsAbsentMinded(const GameInfoset &p_infoset) const override;
   //@}
 
   /// @name Players
@@ -171,7 +173,7 @@ class GameTreeRep : public GameExplicitRep {
 private:
   std::vector<GameNodeRep *> BuildConsistentPlaysRecursiveImpl(GameNodeRep *node);
   void BuildOwnPriorActions() const;
-  void BuildUnreachableNodes();
+  void BuildUnreachableNodes() const;
 };
 
 template <class T> class TreeMixedStrategyProfileRep : public MixedStrategyProfileRep<T> {

src/pygambit/gambit.pxd

@@ -300,6 +300,7 @@ cdef extern from "games/game.h":
         stdvector[c_GameNode] GetPlays(c_GameInfoset) except +
         stdvector[c_GameNode] GetPlays(c_GameAction) except +
         bool IsPerfectRecall() except +
+        bool IsAbsentMinded(c_GameInfoset) except +
 
         c_GameInfoset AppendMove(c_GameNode, c_GamePlayer, int) except +ValueError
         c_GameInfoset AppendMove(c_GameNode, c_GameInfoset) except +ValueError

src/pygambit/infoset.pxi

@@ -161,6 +161,18 @@ class Infoset:
         """Whether the information set belongs to the chance player."""
         return self.infoset.deref().IsChanceInfoset()
 
+    @property
+    def is_absent_minded(self) -> bool:
+        """
+        Whether the information set is absent-minded.
+
+        An information set is absent-minded if there exists a path of play
+        in the game tree that intersects the information set more than once.
+
+        .. versionadded:: 16.5.0
+        """
+        return self.infoset.deref().GetGame().deref().IsAbsentMinded(self.infoset)
+
     @property
     def actions(self) -> InfosetActions:
         """The set of actions at the information set."""

tests/test_extensive.py

@@ -49,39 +49,25 @@ def test_game_add_players_nolabel():
 
 @pytest.mark.parametrize("game_input,expected_result", [
     # Games with perfect recall from files (game_input is a string)
-    ("e01.efg", True),
     ("e02.efg", True),
-    ("cent3.efg", True),
     ("stripped_down_poker.efg", True),
-    ("basic_extensive_game.efg", True),
-
     # Games with perfect recall from generated games (game_input is a gbt.Game object)
     # - Centipede games
-    (games.Centipede.get_test_data(N=3, m0=2, m1=7)[0], True),
     (games.Centipede.get_test_data(N=4, m0=2, m1=7)[0], True),
     # - Two-player binary tree games
-    (games.BinEfgTwoPlayer.get_test_data(level=3)[0], True),
     (games.BinEfgTwoPlayer.get_test_data(level=4)[0], True),
     # - Three-player binary tree games
     (games.BinEfgThreePlayer.get_test_data(level=3)[0], True),
 
     # Games with imperfect recall from files (game_input is a string)
     # - imperfect recall without absent-mindedness
     ("wichardt.efg", False),  # forgetting past action; Wichardt (GEB, 2008)
-    ("noPR-action-selten-horse.efg", False),  # forgetting past action
-    ("noPR-information-no-deflate.efg", False),  # forgetting past information
     ("gilboa_two_am_agents.efg", False),  # forgetting past information; Gilboa (GEB, 1997)
     # - imperfect recall with absent-mindedness
     ("noPR-AM-driver-one-player.efg", False),  # 1 players, one infoset unreached
     ("noPR-AM-driver-two-players.efg", False),  # 2 players, one infoset unreached
     ("noPR-action-AM.efg", False),  # 2 players + forgetting past action; P1 has one infoset
-    ("noPR-action-AM2.efg", False),  # 2 players + forgetting past action; P1 has >1 infoset
     ("noPR-action-AM-two-hops.efg", False),  # 2 players, one AM-infoset each
-
-    # Games with imperfect recall from generated games (game_input is a gbt.Game object)
-    # - One-player binary tree games
-    (games.BinEfgOnePlayerIR.get_test_data(level=3)[0], False),
-    (games.BinEfgOnePlayerIR.get_test_data(level=4)[0], False),
 ])
 def test_is_perfect_recall(game_input, expected_result: bool):
     """

tests/test_infosets.py

@@ -162,3 +162,44 @@ def test_infoset_own_prior_actions(game_file, expected_results):
         }
 
         assert actual_details == expected_set
+
+
+def _get_node_by_path(game, path: list[str]) -> gbt.Node:
+    """
+    Helper to find a node by following a sequence of action labels.
+
+    Parameters
+    ----------
+    path : list[str]
+        A list of action labels in Node->Root order.
+    """
+    node = game.root
+    for action_label in reversed(path):
+        node = node.children[action_label]
+
+    return node
+
+
+@pytest.mark.parametrize("game_input, expected_am_paths", [
+    # Games without absent-mindedness
+    ("e02.efg", []),
+    ("stripped_down_poker.efg", []),
+    ("basic_extensive_game.efg", []),
+    ("gilboa_two_am_agents.efg", []),  # forgetting past information; Gilboa (GEB, 1997)
+    ("wichardt.efg", []),              # forgetting past action; Wichardt (GEB, 2008)
+
+    # Games with absent-mindedness
+    ("noPR-AM-driver-two-players.efg", [[]]),
+    ("noPR-action-AM.efg", [[]]),
+    ("noPR-action-AM-two-hops.efg", [["2", "1", "1", "1", "1"], ["1", "1", "1"]]),
+])
+def test_infoset_is_absent_minded(game_input, expected_am_paths):
+    """
+    Verify the is_absent_minded property of information sets.
+    """
+    game = games.read_from_file(game_input)
+
+    expected_infosets = {_get_node_by_path(game, path).infoset for path in expected_am_paths}
+    actual_infosets = {infoset for infoset in game.infosets if infoset.is_absent_minded}
+
+    assert actual_infosets == expected_infosets

tests/test_node.py

@@ -140,7 +140,7 @@ def _get_path_of_action_labels(node: gbt.Node) -> list[str]:
     (
         "binary_3_levels_generic_payoffs.efg",
         [
-            # Format: ([Path Leaf->Root], (Player Label, Infoset Num, Action Label) or None)
+            # Format: (Path in Node->Root order, (Player Label, Infoset Num, Action Label) or None)
             ([], None),
             (["Left"], None),
             (["Left", "Left"], ("Player 1", 0, "Left")),