Package 'gtree' reference manual

Title:	gtree basic functionality to model and solve games
Description:	gtree basic functionality to model and solve games
Authors:	Sebastian Kranz
Maintainer:	Sebastian Kranz <[email protected]>
License:	GPL >= 2.0
Version:	0.1.1
Built:	2024-11-03 02:48:53 UTC
Source:	https://github.com/skranz/gtree

Specify an action in a stage

Description

Specify an action in a stage

Usage

action(name, set, strategyMethodDomain = NULL, ...)
action(name, set, strategyMethodDomain = NULL, ...)

Arguments

`name`	The variable name of the action
`set`	The set of different action values. Can be a formula that depends on other game variables.
`strategyMethodDomain`	if not NULL the action shall be specified via strategy method in an experiment. State the variable name upon which the action conditions Only used when running an experiment or analysing experimental data

A simple function to define case distinctions

Description

A simple function to define case distinctions

Usage

case_distinction(...)
case_distinction(...)

Return conditional expected equilibrium outcomes

Description

Return conditional expected equilibrium outcomes

Usage

eq_cond_expected_outcomes(game, ..., fixed.list = list(...),
  fixed.vars = NULL, like.factor = NULL)
eq_cond_expected_outcomes(game, ..., fixed.list = list(...),
  fixed.vars = NULL, like.factor = NULL)

Arguments

`game`	the game object for which equilibria were computed e.g. with `game_solve`.
`...`	variable names and their assumed value. We set the probabilities of the conditioned variable values to 1. These correspond to equilibrium outcomes given an unexpected tremble that makes the variables take the specified values. Variables can take multiple values. We then compute conditional equilibrium outcomes for each combination of values
`fixed.list`	Alternativly to ... a named list with values to fix.
`fixed.vars`	Alternative to ... or fixed.list, a vector of variable names. If provided, we compute the conditional expected outcomes holding fixed every possible combination of the variables stated in fixed.vars
`like.factor`	an optional character vector of names of numerical variables that shall be presented like qualitative variables.

Return conditional equilibrium outcomes

Description

Return conditional equilibrium outcomes

Usage

eq_cond_outcomes(game, ..., fixed.list = list(...), fixed.vars = NULL)
eq_cond_outcomes(game, ..., fixed.list = list(...), fixed.vars = NULL)

Arguments

`game`	the game object for which equilibria were computed e.g. with `game_solve`.
`...`	variable names and their assumed value. We set the probabilities of the conditioned variable values to 1. These correspond to equilibrium outcomes given an unexpected tremble that makes the variables take the specified values. Variables can take multiple values. We then compute conditional equilibrium outcomes for each combination of values
`fixed.list`	Alternativly to ... a named list with values to fix.
`fixed.vars`	Alternative to ... or fixed.list, a vector of variable names. If provided, we compute the conditional expected outcomes holding fixed every possible combination of the variables stated in fixed.vars

Return a data frame of expected equilibrium outcomes

Description

Each row will describe a possible expected equilibrium outcome. For numerical variables like payoff_1 the expected value on the equilibrium path is returned.

Usage

eq_expected_outcomes(game, like.factor = NULL)
eq_expected_outcomes(game, like.factor = NULL)

Arguments

`game`	the game object for which prevoiously equilibria were computed e.g. with `game_solve`.
`like.factor`	an optional character vector of names of numerical variables that shall be presented like qualitative variables.

Details

For qualitative variables, we generate a string like "accept(0.3),reject(0.2)" describing the moves that occur with positive probability and those probabilities on the equilibrium path.

Return the computed equilibria using the internal representation

Description

Return the computed equilibria using the internal representation

Usage

eq_li(game, ...)
eq_li(game, ...)

Return a data frame of all equilibrium outcomes

Description

If we have mixed strategies or moves of nature an equilibrium outcome will consist of several rows. One row for each pure outcome that occurs with positive probability.

Usage

eq_outcomes(game, add.move.probs = FALSE)
eq_outcomes(game, add.move.probs = FALSE)

Arguments

`game`	the game object for which previously equilibria were computed e.g. with `game_solve`.
`add.move.probs`	if `TRUE` add for each action (and move of nature) the probability that the actual value has been chosen in the corresponding information set (node).

Details

Typically eq_expected_outcomes will deliver a version that is easier to read. It will take expected values and reduce each outcome to one row.

Yet eq_outcomes may be more useful for automatical analysis.

Return solved equilibrium in a table format

Description

Best take a look at the Vignettes to understand this format.

Usage

eq_tables(game, reduce.tables = TRUE, combine = 2,
  eq.ind = seq_along(game$eq.li), ignore.keys = NULL,
  eq.li = game$eq.li[eq.ind], ...)
eq_tables(game, reduce.tables = TRUE, combine = 2,
  eq.ind = seq_along(game$eq.li), ignore.keys = NULL,
  eq.li = game$eq.li[eq.ind], ...)

Arguments

`reduce.tables`	(default = TRUE). Shall we try to reduce the rows and columns of the key tables be reduced to get a subset of neccessary keys that perfectly predict the chosen value of an action?
`combine`	if 0 generate separate tables for each equilibrium. If 1 bind the tables of each variable over all equilibria. If 2 (default) also collapse the rows that are the same for different equilibria and add a column eq.inds that contains all equilibrium numbers as a comma separated string
`eq.ind`	Vector of integers specifying the indices of all equilibria that shall be considered. By default all equilibria.
`ignore.keys`	A character vector of variables that will always be removed from the key variables, without any check whether they are neccessary or not.

Changes one or several parameters of a game

Description

For an already compiled game, we try to change parameters in a fashion that is faster than a complete recompilation.

Usage

game_change_param(game, ..., params = list(),
  verbose = isTRUE(game$options$verbose > 0))
game_change_param(game, ..., params = list(),
  verbose = isTRUE(game$options$verbose > 0))

Compile a game defined with `new_game`

Description

Compile a game defined with new_game

Usage

game_compile(game, branching.limit = 10000, for.internal.solver = FALSE,
  add.sg = for.internal.solver, add.spi = for.internal.solver,
  add.spo = for.internal.solver, force = FALSE,
  verbose = game$options$verbose, ...)
game_compile(game, branching.limit = 10000, for.internal.solver = FALSE,
  add.sg = for.internal.solver, add.spi = for.internal.solver,
  add.spo = for.internal.solver, force = FALSE,
  verbose = game$options$verbose, ...)

Make a deep copy of a game

Description

Make a deep copy of a game

Usage

game_copy(game)
game_copy(game)

Set add a large amount of utility if a player plays a particular action

Description

Allows to study the game under the assumption that a player strongly prefers to chose one particular move of an action variable.

Usage

game_fix_action_preferences(game, ..., actions = list(...), util.add = 1000)
game_fix_action_preferences(game, ..., actions = list(...), util.add = 1000)

Arguments

`...`	directly the named arguments from which `actions` will be constructed
`actions`	a named list. The names correspond to action names and the values either to fixed values of the action or to a formula. If it is a formula the action value can depend on earlier computed variables.

Details

If you want to fix mixed strategies, use the he related function game_fix_action_preferences transforms the corresponding action into a move of nature.

For fixing pure strategies game_fix_action_preferences is preferable when using the gambit-logit solver that can find sequential equilibria, by using logit trembles.

Fix move probabilities of actions

Description

The function corresponds the provided actions into moves of nature with specified move probabilities. Can be a useful step when checking for existence of equilibria with particular structure.

Usage

game_fix_actions(game, ..., actions = list(...), tremble.prob = NULL)
game_fix_actions(game, ..., actions = list(...), tremble.prob = NULL)

Arguments

`...`	directly the named arguments from which `actions` will be constructed
`actions`	a named list. The names correspond to action names. The default value to fix mixed strategies is a table that specifies conditional move probabilities (see example). If you want to fix pure actions you can also provide arguments as in `game_fix_action_preferences`.
`tremble.prob`	If a positive number, we assume that with this probability the player trembles and then chooses a random action with uniform probability. Trembles can be useful to enforce some sequential rationality in continuation play, but note that uniform trembles are not neccessarily the correct form of trembles to find sequential equilibria or trembling hand perfect equilibria.

Details

For fixing pure strategies game_fix_action_preferences is preferable when using the gambit-logit solver that can find sequential equilibria, by using logit trembles.

Solve equilibria of a game using Gambit

Description

You need to install Gambit http://www.gambit-project.org to use this function.

Usage

game_gambit_solve(game, gambit.command = NULL, mixed = FALSE,
  just.spe = TRUE, qre.lambda = NULL,
  gambit.dir = first.non.null(getOption("gtree.gambit.dir"), ""),
  efg.dir = NULL, efg.file = NULL, verbose = isTRUE(game$options$verbose
  >= 1), add.q.flag = TRUE, ...)
game_gambit_solve(game, gambit.command = NULL, mixed = FALSE,
  just.spe = TRUE, qre.lambda = NULL,
  gambit.dir = first.non.null(getOption("gtree.gambit.dir"), ""),
  efg.dir = NULL, efg.file = NULL, verbose = isTRUE(game$options$verbose
  >= 1), add.q.flag = TRUE, ...)

Arguments

`game`	the game object created with new_game
`gambit.command`	A Gambit command line command with options but not file name. For example `"gambit-enummixed -q"` to compute all extreme point mixed equilibria. The different Gambit command line solvers are described here: http://www.gambit-project.org/gambit16/16.0.0/tools.html If left as NULL a default gambit command line solver with appropriate arguments will be chosen, depending on your arguments for mixed and just.spe
`mixed`	relevant if no explicit gambit.command is given. If FALSE (default) only pure strategy equilibria will be computed, otherwise try to compute one mixed equilibrium.
`just.spe`	if TRUE compute only SPE. If FALSE all NE will be computed.
`qre.lambda`	if not NULL compute a logit QRE equilibrium using the gambit-logit solver and the specified value of lambda.
`gambit.dir`	The directory where to find the Gambit command line solvers. Ideally, you put this directory into the search path of your system and can keep the default `gambit.dir = ""`. To globally change the default directory adapt the following code `options(gtree.gambit.dir = "/PATH/TO/GAMBIT")`
`efg.dir`	To solve via Gambit we first write the game tree into an .efg file. If `efg.dir` is NULL (default), the file will be written to a temporary directory. But you can also specify a custom directory here, e.g. if you want to take a look at the file.
`efg.file`	If NULL a default file name for the efg file will be generated based on the name of the game and the specified preferences. But you can specify a custom name here.
`verbose`	if TRUE show some extra information
`add.q.flag`	The gambit command line solver should always be called with the option "-q" for gtree to be able to parse the returned output. If add.q.flag is TRUE we will add this flag if you have not yet added it to your `gambit.command`

Solve for quantal response equilibria using Gambit

Description

This function computes logit agent quantal response equilibria using the Gambit solver gambit-logit. For a short description see the Wikipedia article and the gambit-logit solver's https://gambitproject.readthedocs.io/en/latest/tools.html#gambit-logit-compute-quantal-response-equilbria. Details are in the article https://link.springer.com/article/10.1007/s00199-009-0443-3 by Theodore Turocy. But unfortunately, the article can only be found behind a pay wall.

Usage

game_gambit_solve_qre(game, gambit.command = "gambit-logit -q -l",
  gambit.dir = "", efg.file = NULL, efg.dir = NULL,
  verbose = isTRUE(game$options$verbose >= 1))
game_gambit_solve_qre(game, gambit.command = "gambit-logit -q -l",
  gambit.dir = "", efg.file = NULL, efg.dir = NULL,
  verbose = isTRUE(game$options$verbose >= 1))

Details

For a description of the arguments see game_gambit_solve

Set add a large amount of utility if a player plays a particular action

Description

Allows to study the game under the assumption that a player strongly prefers to chose one particular move of an action variable.

Usage

game_prefer_outcomes(game, player1 = NULL, player2 = NULL, player3 = NULL,
  ..., player.prefs = list(player1 = player1, player2 = player2, player3 =
  player3, ...))
game_prefer_outcomes(game, player1 = NULL, player2 = NULL, player3 = NULL,
  ..., player.prefs = list(player1 = player1, player2 = player2, player3 =
  player3, ...))

Arguments

`player1`	A formula describing which utility levels should be added to the current utility function of player 1 (see example). If NULL we don't add utilities for player 1. Similar for the other players 2-4.
`...`	additional formulas for games with more than 4 players.
`player.prefs`	by default equal to `list(player1,player2,player3, player4,...)`. Can be manually provided.

Details

If you want to fix mixed strategies, use the he related function game_fix_action_preferences transforms the corresponding action into a move of nature.

For fixing pure strategies game_fix_action_preferences is preferable when using the gambit-logit solver that can find sequential equilibria, by using logit trembles.

Change options of an already created game object

Description

See make_game_options for a description of the available options.

Usage

game_set_options(game, ...)
game_set_options(game, ...)

Set players' preferences

Description

This function sets players preferences to a parametrized preference type. To specify completely custom preferences use game_set_util_fun instead.

Usage

game_set_preferences(game, pref)
game_set_preferences(game, pref)

Arguments

`game`	The game object
`pref`	A preference created with a function starting with `pref_`, like e.g. `pref_ineqAv(alpha=1, beta=0.5)`. Use `pref_custom` to specify custom preferences.

Solve equilibria of a game

Description

With the default arguments the internal gtree solver is used to find all pure strategy subgame perfect equilibria of the game.

Usage

game_solve_spe(game, mixed = FALSE, just.spe = TRUE, use.gambit = mixed |
  !just.spe, verbose = isTRUE(game$options$verbose >= 1),
  gambit.command = NULL, ...)
game_solve_spe(game, mixed = FALSE, just.spe = TRUE, use.gambit = mixed |
  !just.spe, verbose = isTRUE(game$options$verbose >= 1),
  gambit.command = NULL, ...)

Arguments

`game`	the game object created with new_game
`use.gambit`	solve via Gambit. Changing `mixed` or `just.spe` or specifying a `gambit.command` has only impact if `use.gambit=TRUE`. See `game_gambit_solve` for details.

Write game as a Gambit efg file

Description

Write game as a Gambit efg file

Usage

game_write_efg(game, file.with.dir = file.path(dir, file),
  file = tg.efg.file.name(game$tg), dir = getwd(),
  verbose = !isTRUE(game$options$verbose == 0))
game_write_efg(game, file.with.dir = file.path(dir, file),
  file = tg.efg.file.name(game$tg), dir = getwd(),
  verbose = !isTRUE(game$options$verbose == 0))

Arguments

`game`	The game object
`file.with.dir`	The file with full path. If NULL create a default name
`file`	The file name without directory
`dir`	The directory of a file

Return a data frame of all possible outcomes

Description

Return a data frame of all possible outcomes

Usage

get_outcomes(game, reduce.cols = TRUE)
get_outcomes(game, reduce.cols = TRUE)

Arguments

`game`	the game object defined with `new_game` and being compiled with `game_compile` or after a call of `game_solve`.
`reduce.cols`	if TRUE remove some technical columns

Returns logical vector replacing NA by FALSE

Description

Returns logical vector replacing NA by FALSE

Usage

is_true(vec)
is_true(vec)

Arguments

vec

A vector of logical values (possible containing NA) or values that can be transformed to logicals

Specify the game options inside `new_game`

Description

Specify the game options inside new_game

Usage

make_game_options(verbose = TRUE, ...)
make_game_options(verbose = TRUE, ...)

Specify the game parameters This function is only to be used inside `new_game`. To change the parameters of an existing game call `game_change_params`.

Description

Specify the game parameters This function is only to be used inside new_game. To change the parameters of an existing game call game_change_params.

Usage

make_game_params(numPlayers = 2, ...)
make_game_params(numPlayers = 2, ...)

Specify a random move of nature in a stage

Description

Specify a random move of nature in a stage

Usage

natureMove(name, set, probs = NULL, table = NULL, fixed = NULL,
  tremble.prob = NULL, ...)
natureMove(name, set, probs = NULL, table = NULL, fixed = NULL,
  tremble.prob = NULL, ...)

Arguments

`name`	The variable name of the variable
`set`	The set of different values. Can be a rhs only formula.
`probs`	The probability of each element in set. If NULL all moves are equally likely. Can be a rhs formula

Create a new gtree game

Description

See the examples on gtree website for detailed explanation.

Usage

new_game(gameId, params = game_params(), options = make_game_options(),
  stages, variant = "", check = TRUE)
new_game(gameId, params = game_params(), options = make_game_options(),
  stages, variant = "", check = TRUE)

Change the parameters of a preference object

Description

Change the parameters of a preference object

Usage

pref_change_params(pref, ..., params = list(), label = NULL,
  players = 1:2, numPlayers = length(players))
pref_change_params(pref, ..., params = list(), label = NULL,
  players = 1:2, numPlayers = length(players))

Create a custom preference

Description

Create a custom preference

Usage

pref_custom(..., params = NULL, label = "custom")
pref_custom(..., params = NULL, label = "custom")

Arguments

`...`	Unquoted that describe the utility as a function of the parameters of the game and possible preference parameters. Should be ordered by players. Names are irrelevant.
`params`	An optional list of parameters that are used in the formulas above
`label`	A label for the preference, should contain info about the parameters
`type`	A general type label independet of the parameters

Fehr-Schmidt inequality aversion with envy only

Description

Fehr-Schmidt inequality aversion with envy only

Usage

pref_envy(alpha = 0, player = 1:numPlayers, numPlayers = 2, ...)
pref_envy(alpha = 0, player = 1:numPlayers, numPlayers = 2, ...)

Arguments

`alpha`	the degree of envy
`player`	player(s) for which the preferences apply. Per default 1:2
`numPlayers`	number of players in game per default 2

Combine preferences for different players

Description

Combine preferences for different players

Usage

pref_heterogeneous_players(..., prefs = list(...), label = NULL)
pref_heterogeneous_players(..., prefs = list(...), label = NULL)

Arguments

`...`	all preferences ordered by players
`prefs`	alternatively the preferences as a list object
`label`	optional label of preferences. If NULL the individual labels will be pasted together
`type`	label of the combined preference type

Fehr-Schmidt inequality aversion.

Description

Fehr-Schmidt inequality aversion.

Usage

pref_ineqAv(alpha = 0, beta = 0, player = 1:numPlayers, numPlayers = 2,
  ...)
pref_ineqAv(alpha = 0, beta = 0, player = 1:numPlayers, numPlayers = 2,
  ...)

Arguments

`alpha`	the degree of envy
`beta`	the degree of guilt
`player`	player(s) for which the preferences apply. Per default 1:2
`numPlayers`	number of players in game per default 2

'Linear loss aversion preferences with a single reference point

Description

'Linear loss aversion preferences with a single reference point

Usage

pref_lossAv(lambda = 2, r = 0, player = 1:numPlayers, numPlayers = 2)
pref_lossAv(lambda = 2, r = 0, player = 1:numPlayers, numPlayers = 2)

Arguments

`lambda`	factor by which losses loom larger than gains (default = 2)
`r`	The reference point, by default 0. Can be a vector in order to have different reference points for different players.
`player`	player(s) for which the preferences apply. Per default 1:2
`numPlayers`	number of players in game per default 2

Utility is equal to monetary payoff.

Description

This means the player is simply a risk neutral expected payoff maximizer.

Usage

pref_payoff(player = 1:2, ...)
pref_payoff(player = 1:2, ...)

Arguments

player

player(s) for which the preferences apply. Per default 1:2

Specify a stage for a game

Description

Specify a stage for a game

Usage

stage(name, player = NULL, condition = NULL, observe = NULL,
  compute = NULL, nature = NULL, actions = NULL, ...)
stage(name, player = NULL, condition = NULL, observe = NULL,
  compute = NULL, nature = NULL, actions = NULL, ...)

Arguments

`name`	Name of the stage
`player`	The player who acts in this stage. Can be a rhs formula. If an action is chosen in the stage, there must be a unique player. If it is a stage in which no actions take place, the player variable multiple players can be set. Each player observes the variables specified under observe.
`condition`	A logical condition specifying whether the stage will be run. Can be a rhs formula. If it evaluates to FALSE the stage will not be shown, i.e. no observations are made and no actions are chosen. Also no computations in this stage take place.
`observe`	A vector of variable names specifying which variables are observed by the player(s) at this stage. Is relevant to correctly specify the information sets in the extensive form game.
`compute`	A list of formulas like 'compute=list(payoff_1 ~ x-5)'. The lhs specifies a variable name and the rhs a DETERMINISTIC formula. The variables are computed at the beginning of the stage before actions and moves of nature take place. This means they can be used e.g. in formulas for action sets of the same stage.
`nature`	A list of moves of nature, i.e. random variables from a finite set. E.g. nature=list(natureMove("proposer",c(1,2),prob=c(0.4,0.6)).
`actions`	A list of actions. E.g. actions=list(action("offer",~0:cake_size)

Package 'gtree'

Help Index

Specify an action in a stage

Description

Usage

Arguments

See Also

A simple function to define case distinctions

Description

Usage

See Also

Return conditional expected equilibrium outcomes

Description

Usage

Arguments

See Also

Return conditional equilibrium outcomes

Description

Usage

Arguments

See Also

Return a data frame of expected equilibrium outcomes

Description

Usage

Arguments

Details

See Also

Return the computed equilibria using the internal representation

Description

Usage

See Also

Return a data frame of all equilibrium outcomes

Description

Usage

Arguments

Details

See Also

Return solved equilibrium in a table format

Description

Usage

Arguments

See Also

Changes one or several parameters of a game

Description

Usage

See Also

Compile a game defined with new_game

Description

Usage

See Also

Make a deep copy of a game

Description

Usage

See Also

Set add a large amount of utility if a player plays a particular action

Description

Usage

Arguments

Details

See Also

Fix move probabilities of actions

Description

Usage

Arguments

Details

See Also

Solve equilibria of a game using Gambit

Description

Usage

Arguments

See Also

Solve for quantal response equilibria using Gambit

Description

Usage

Details

See Also

Set add a large amount of utility if a player plays a particular action

Description

Usage

Arguments

Compile a game defined with `new_game`

Specify the game options inside `new_game`

Specify the game parameters This function is only to be used inside `new_game`. To change the parameters of an existing game call `game_change_params`.