Deep CFR self-play anchor safe 512x3 2x updates 10000 iter config 및 관련 변경

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
This commit is contained in:
2026-05-07 09:14:23 +09:00
co-authored by Claude Haiku 4.5
parent c779621823
commit fd99d3bb4a
3 changed files with 152 additions and 5 deletions
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run:
experiment_name: lost_cities_deep_cfr_selfplay_anchor_safe_512x3_2x_updates_10000iter
iterations: null
seed: 79
max_iterations: 10000
max_hours: null
device: cuda
use_amp: false
rules:
n_colors: 5
n_ranks: 9
min_rank: 2
n_handshakes: 3
hand_size: 8
expedition_penalty: -20
bonus_threshold: 8
bonus_amount: 20
encoding:
derived_playability: true
slot_aware_playability: true
network:
hidden_size: 512
num_layers: 3
activation: relu
traversal:
traversals_per_iteration: 2
traversals_per_player: 70
max_depth: null
max_nodes: 10000
max_nodes_per_traversal: 1000
regret_matching_epsilon: 0.0001
outcome_sampling_epsilon: 0.2
outcome_sampling_value_clip: 500.0
outcome_unsampled_regret: zero
cutoff_value_mode: score_diff
cutoff_rollouts: 0
cutoff_rollout_policy: random
cutoff_rollout_max_steps: 300
opponent_policy: self_play_league
strategy_sample_interval: 1
store_strategy_on_traverser_nodes: true
store_strategy_on_opponent_nodes: false
num_workers: 8
worker_chunk_size: 4
traversal_worker_chunk_size: 8
progress_every_traversals: 10
endpoint_depth_bucket_width: 100
endpoint_depth_bucket_max: 1000
regret_matching:
all_negative_fallback: argmax_tiebreak
training_weighting:
mode: none
self_play:
snapshot_every: 1
max_snapshots: 20
anchor_probability: 0.0
current_weight: 0.45
recent_weight: 0.30
older_weight: 0.15
anchor_weight: 0.10
recent_window: 5
optimization:
advantage_train_steps: 1
strategy_train_steps: 1
batch_size: 32
advantage_batch_size: 1024
strategy_batch_size: 1024
advantage_updates_per_iteration: 512
strategy_updates_per_iteration: 512
learning_rate: 0.00003
weight_decay: 0.0001
grad_clip: 1.0
memory:
advantage_capacity: 2000000
strategy_capacity: 2000000
checkpoint:
directory: runs/deep_cfr/deep_cfr_selfplay_anchor_safe_512x3_2x_updates_10000iter
save_latest: true
save_every_iteration: false
save_iteration_interval: 100
save_latest_only: false
progress_interval_seconds: 20.0
exact_resume: false
evaluation:
eval_every: 5
games: 100
opponents:
- random
- passive_discard
- safe_heuristic
- safe_heuristic_loose
- safe_heuristic_strict
- noisy_safe
max_steps: 10000
on_max_steps: score_diff
batch_size: 64
device: trainer
num_workers: 4