Package: RelationalContracts 0.2.0

RelationalContracts: Characterize relational contracts in repated or stochastic games

Characterize relational contracts in repated or stochastic games. Can also analyse repeated negotiation equilibria.

Authors:Sebastian Kranz

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RelationalContracts.pdf |RelationalContracts.html✨
RelationalContracts/json (API)

# Install 'RelationalContracts' in R:

install.packages('RelationalContracts', repos = c('https://skranz.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/skranz/relationalcontracts/issues

On CRAN:

dynamic-game economics game-theory hold-up nash-equilibrium repeated-game stochastic-game

2.48 score 4 stars 15 scripts 154 exports 25 dependencies

Last updated 4 years agofrom:e29d080e8b (on master). Checks:OK: 1 WARNING: 6. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Sep 22 2024
R-4.5-win	WARNING	Sep 22 2024
R-4.5-linux	WARNING	Sep 22 2024
R-4.4-win	WARNING	Sep 22 2024
R-4.4-mac	WARNING	Sep 22 2024
R-4.3-win	WARNING	Sep 22 2024
R-4.3-mac	WARNING	Sep 22 2024

Exports:A1A2.to.a.grid add.action.details add.eqs.labs add.rel.multistage.compile add.rne.action.labels add.to.rel.defs add.to.rel.list advanced.paste.matrix.cols animate_capped_rne_history animate_eq_li approxeq arms.race.example assert.action.names capped.rne.iterations capped.rne.multistage.iterations capped.rne.period.T check.rel check.rel.colnames check.rel.has.colscolnames compare_eq compile.sdf compile.sdf.classic compute.after.cap.action.inds compute.delta.rho compute.eq.trans.mat compute.na compute.optimal.payoffs.from.actions compute.optimal.payoffs.from.eq.actions compute.payoff.for.state compute.rep.game.action.lists compute.rep.game.nash.threats compute.x.trans.mat deparse1 diagnose_transitions dyngame.sol.to.rel.sol eq_combine_xgroup eq_diagram eq_diagram_xgroup eq.a.to.ax eq.ax.to.a eq.li.compare eval.rel.expression example.relhold example.rne examples.diagnose examples.eq_diagram examples.joint_independent examples.multistage examples.multistage.spe.trunc examples.rel_state_probs examples.rel.spe examples.rne_capped examples.spe.trunc expand_grid expand.grid2 extend.range factor.cols.as.strings find.best.reply.payoffs find.cycles find.eq.chain.x find.eq.li.action.repetitions find.same.eqs find.static.a.for.all.x find.static.ci.for.all.x find.static.G.for.all.x find.static.payoffs.for.all.x first.non.null get_capped_history get_eq get_mpe get_repgames_results get_rne get_rne_details get_spe get_T_rne_history get.def.x has.col has.cols irv irv_joint_dist irv_val make.ax.labels make.rel.dyngame make.rsg.game make.state.lab.a make.state.lab.ai match.by.cols mpe.example nlist non.null num.cycles.of.length old.make.state.lab.a paste.df.cols paste.matrix.cols plot_eq_payoff_set plot.eqs plot.rne.payoff.set plot.rsg.payoff.set prepare.after.cap prepare.for.spe print.relgame quick_df r_rne_find_actions r.capped.rne.iterations r.capped.rne.multistage.iterations r.pl1.ax.best.reply.payoffs r.pl2.ax.best.reply.payoffs r.which.chunk.maxs rel_after_cap_actions rel_after_cap_payoffs rel_capped_rne rel_capped_rne_old rel_change_param rel_compile rel_eq_as_discounted_sums rel_first_best rel_game rel_is_eq_rne rel_mpe rel_options rel_param rel_rne rel_rne_from_capped rel_rne_from_eq_actions rel_scale_eq_payoffs rel_solve_repgames rel_spe rel_spe_classic rel_state rel_state_probs rel_states rel_T_rne rel_transition rel.capped.rne.multistage.old rep.games.to.rne.df scale.eq.payoffs simulate.eq sizes.to.chunk.inds solve.weakly.directional.state solve.x.rep.multistage solve.x.repgame solve.x.repgame.external static.nash.eq study_convergence study_convergene_example trans.mat.mult trne_cycle_info trunc_policy_iteration trunc.spe.cheating.payoffs trunc.spe.full.dyn.vi trunc.spe.harshest.punishment trunc.spe.highest.U which.chunk.maxs xrow.a.to.ax

Dependencies:cli cpp11 dplyr fansi generics glue lifecycle magrittr matrixStats pillar pkgconfig purrr R6 Rcpp RelationalContractsCpp restorepoint rlang stringi stringr tibble tidyr tidyselect utf8 vctrs withr

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Use ggplotly to show an animation of the payoff sets of a capped RNE going from t=T to t=1	animate_capped_rne_history
Use ggplotly to show an animation of the payoff sets of a list of equilibria	animate_eq_li
Helper function to find differences between two equilibria	compare_eq
Take a look at the computed transitions for each state using separate data frames	diagnose_transitions
Aggregate equilibrium behavior in games with random active player	eq_combine_xgroup
Draws a diagram of equilibrium state transition	eq_diagram
Draws a diagram of equilibrium state transition	eq_diagram_xgroup
Get the last computed equilibrium of game g	get_eq
Get the results of all solved repeated games assuming the state is fixed	get_repgames_results
Get the last computed RNE of game g	get_rne
Retrieve more details about the last computed RNE	get_rne_details
Get the last computed SPE of game g	get_spe
Get the intermediate steps in from t = T to t = 1 for a T-RNE or capped RNE that has been solved with 'save.history = TRUE'	get_T_rne_history
Helper functions to specify state transitions	irv
Helper function to specify state transitions	irv_joint_dist
Helper functions to specify state transitions	irv_val
Show a base R plot of equilibrium payoff set	plot_eq_payoff_set
Fix action profiles for the equilibrium path (ae) and during punishment (a1.hat and a2.hat) that are assumed to be played after the cap in period T onwards. The punishment profile a1.hat is the profile in which player 1 already plays a best-reply (in a1 he might play a non-best reply). From the specified action profiles in all states, we can compute the relevant after-cap payoffs U(x), v1(x) and v2(x) assuming that state transitions would continue.	rel_after_cap_actions
Specify the SPE payoff set(s) of the truncated game(s) after a cap in period T. While we could specify a complete repeated game that is played after the cap, it also suffices to specify just an SPE payoff set of the truncated game of the after-cap state.	rel_after_cap_payoffs
Solve an RNE for a capped version of a game	rel_capped_rne
Add parameters to a relational contracting game	rel_change_param
Compiles a relational contracting game	rel_compile
Translate equilibrium payoffs as discounted sum of payoffs	rel_eq_as_discounted_sums
Compute first-best.	rel_first_best
Creates a new relational contracting game	rel_game
Checks if an equilibrium eq with negotiation payoffs is an RNE	rel_is_eq_rne
Tries to find a MPE by computing iteratively best replies	rel_mpe
Set some game options	rel_options
Add parameters to a relational contracting game	rel_param
Find an RNE for a (weakly) directional game	rel_rne
Scale equilibrium payoffs	rel_scale_eq_payoffs
Solves for all specified states the repeated game assuming the state is fixed	rel_solve_repgames
Finds an optimal simple subgame perfect equilibrium of g. From this the whole SPE payoff set can be deduced.	rel_spe
Compute the long run probability distribution over states if an equilibrium is played for many periods.	rel_state_probs
Add one or multiple states. Allows to specify action spaces, payoffs and state transitions via functions	rel_state rel_states
Compute a T-RNE	rel_T_rne
Add a state transition from one state to one or several states. For more complex games, it may be preferable to use the arguments 'trans.fun' of 'link{rel_states}' instead.	rel_transition