Adaptive ranking resume

Resume a previously persisted adaptive pairing session.

Usage

adaptive_rank_resume(session_dir, ...)

Arguments

session_dir

Directory containing session artifacts.

...

Reserved; must be empty. Resume uses persisted predictive priors.

Value

An adaptive_state object restored from disk.

Details

This is a thin wrapper around load_adaptive_session() and performs schema and log-shape checks during load. Returned state preserves canonical step_log, round_log, and item_log contents used for adaptive auditability. The saved predictive mode, prior, pairing strategy, current TrueSkill state, and connected shuffled bootstrap queue are authoritative. Resume does not reload a predictive model or regenerate its predictions.

See also

make_warm_start_prior(), adaptive_rank_start(), adaptive_rank_run_live(), save_adaptive_session(), load_adaptive_session()

Other adaptive ranking: adaptive_rank(), adaptive_rank_run_live(), adaptive_rank_start(), make_adaptive_judge_llm(), make_adaptive_judge_replay(), make_adaptive_replay_reservoir(), summarize_adaptive(), validate_adaptive_replay()

Examples

dir <- tempfile("pwllm-session-")
state <- adaptive_rank_start(c("a", "b", "c"), seed = 3)
save_adaptive_session(state, dir, overwrite = TRUE)
restored <- adaptive_rank_resume(dir)
summarize_adaptive(restored)
#> # A tibble: 1 × 6
#>   n_items steps_attempted committed_pairs n_refits last_stop_decision
#>     <int>           <int>           <int>    <int> <lgl>             
#> 1       3               0               0        0 FALSE             
#> # ℹ 1 more variable: last_stop_reason <chr>