pygambit.gambit.Game

class pygambit.gambit.Game

A game, the fundamental unit of analysis in game theory.

Games may be represented in extensive or strategic form.

Methods

append_event(nodes, actions)	Add a chance move at terminal nodes, with actions and their probabilities given by actions.
append_infoset(nodes, infoset)	Add a move at terminal nodes, joining the information set that the node identified by infoset belongs to.
append_move(nodes, player, actions)	Add a move for player at terminal nodes.
behavior_support_profile([actions])	Create a new BehaviorSupportProfile on the game.
copy_tree(src, dest)	Copy the subtree rooted at the node identified by src to the node identified by dest.
delete_parent(node)	Delete the parent of the node identified by node.
delete_tree(node)	Truncate the game tree at the node identified by node, deleting the subtree beneath it.
from_arrays(*arrays[, title])	Create a new Game with a strategic representation.
from_dict(payoffs[, title])	Create a new Game with a strategic representation.
get_action_probs(history)	Returns the probability of each action at the node that history resolves to, keyed by label, if it currently belongs to a chance event.
get_actions(history)	Returns the labels of the actions available at the node that history resolves to, in the order they are defined.
get_behavior(player, strategy)	Return the mapping from information sets to actions prescribed by a strategy.
get_events()	Returns a snapshot of the chance player's events: the points of exogenous randomness, each with a probability distribution over its actions.
get_histories(selector)	Returns the Histories of the nodes that selector resolves to.
get_infosets(player)	Returns a snapshot of the information sets belonging to the personal player player: the decisions at which that player chooses an action.
get_max_payoff(player)	Returns the largest payoff for player in any play of the game.
get_members(history)	Returns the Histories of the nodes which are members of the information set or event that the node identified by history currently belongs to.
get_min_payoff(player)	Returns the smallest payoff for player in any play of the game.
get_minimal_subgame(history)	Returns the History of the root of the smallest subgame containing the information set or event that the node identified by history belongs to.
get_outcome(location)	Returns the label of the outcome attached at location.
get_outcome_payoffs(label)	Returns the payoff to each player at the outcome labeled label.
get_outcomes()	Returns the labels of the outcomes in the game.
get_payoffs(contingency)	Returns the payoff to each player at a pure-strategy contingency.
get_player(history)	Returns the label of the player associated with the node that history resolves to: the one who makes the decision, if this is a personal node, or the chance player, if this is an event.
get_strategies(player)	Returns a snapshot of the labels of the strategies belonging to player.
get_strategy_unreachable()	Returns the Histories of the nodes that are not reachable by any pure strategy profile.
get_subgame_roots()	Returns the Histories of the roots of the subgames of the game, in postorder (children before parents).
has_perfect_recall(player)	Returns whether player has perfect recall.
insert_event(node, actions)	Insert a chance move prior to the node identified by node, with actions and their probabilities given by actions.
insert_infoset(node, infoset)	Insert a move in the information set or event that the node identified by infoset belongs to, prior to the node identified by node.
insert_move(node, player, actions)	Insert a move for player prior to the node identified by node, with actions labeled according to actions.
make_event(nodes, probs[, label])	Form nodes into a single event with distribution probs.
make_infoset(nodes, player[, label])	Form nodes into a single information set belonging to player.
make_outcome(location, payoffs, label)	Create an outcome with payoffs and label and attach it at location.
make_outcome_null(location)	Reset the outcome at location to the null outcome.
mixed_behavior_profile([data, rational])	Create a mixed behavior profile over the game.
mixed_strategy_profile([data, rational])	Create a mixed strategy profile over the game.
move_tree(src, dest)	Move the subtree rooted at the node identified by src to the node identified by dest.
new_table(dim[, title])	Create a new Game with a strategic representation.
new_tree([players, title])	Create a new Game consisting of a trivial game tree, with one node, which is both root and terminal.
random_behavior_profile([denom, gen])	Create a MixedBehaviorProfile on the game, with probabilities drawn from the uniform distribution over the set of mixed behavior profiles.
random_strategy_profile([denom, gen])	Create a MixedStrategy on the game, with probabilities drawn from the uniform distribution over the set of mixed strategy profiles.
relabel_actions(infoset, labels[, strict])	Simultaneously reassign the labels of actions at the information set or event that the node identified by infoset belongs to.
relabel_outcomes(labels[, strict])	Simultaneously reassign the labels of the game's outcomes.
relabel_players(labels[, strict])	Simultaneously reassign the labels of the game's players.
relabel_strategies(player, labels[, strict])	Simultaneously reassign the labels of player's strategies.
set_event_actions(event, probs[, drop, add])	Set the actions at the event that the node identified by event belongs to, to be the keys of probs, in order, with the given probability distribution.
set_move_actions(infoset, actions[, drop, add])	Set the actions at the move that the node identified by infoset belongs to, to be actions, matching by label.
set_outcome_payoffs(label, payoffs)	Sets the payoff to each player at the outcome labeled label.
set_players(players[, drop, add])	Set the players of the game to be players, matching by label.
set_strategies(player, strategies[, drop, add])	Set the strategies of player to be strategies, matching by label.
strategy_support_profile([strategies])	Create a new StrategySupportProfile on the game.
to_arrays(dtype)	Generate the payoff tables for players represented as numpy arrays.
to_efg([filepath_or_buffer])	Save the game to an .efg file or return its serialized representation
to_html([filepath_or_buffer])	Export the game to HTML format.
to_latex([filepath_or_buffer])	Export the game to LaTeX format.
to_nfg([filepath_or_buffer])	Save the game to a .nfg file or return its serialized representation

Attributes

contingencies	An iterator over the contingencies in the game.
description	Get or set the description of the game.
is_const_sum	Whether the game is constant sum.
is_perfect_recall	Whether the game is perfect recall.
is_tree	Return whether a game has a tree-based representation.
max_payoff	The maximum payoff to any player in any play of the game.
min_payoff	The minimum payoff to any player in any play of the game.
players	The set of players in the game.
title	Get or set the title of the game.