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authorYurenHao0426 <blackhao0426@gmail.com>2026-06-29 12:15:51 -0500
committerYurenHao0426 <blackhao0426@gmail.com>2026-06-29 12:15:51 -0500
commita6ec4288a2232988b130b2f00bb2565f81706966 (patch)
tree1bb86e7f0b899b823b9e7fdf383e832d30a181e0 /flossing_suite/results/toy_rnn
Recursive reasoning dynamics: analysis pipeline, paper drafts, toy models
Failure=more-chaotic (task-general under validity labeling) reduces to convergence/completeness detection; mechanism (transient chaos vs multistability vs input-induced) under investigation. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Diffstat (limited to 'flossing_suite/results/toy_rnn')
-rwxr-xr-xflossing_suite/results/toy_rnn/toy_baseline_no_floss_N80_k40_E1000.cmd.sh43
-rwxr-xr-xflossing_suite/results/toy_rnn/toy_pre_inter_N80_k40_E1000.cmd.sh43
-rwxr-xr-xflossing_suite/results/toy_rnn/toy_prefloss_N80_k40_E1000.cmd.sh43
3 files changed, 129 insertions, 0 deletions
diff --git a/flossing_suite/results/toy_rnn/toy_baseline_no_floss_N80_k40_E1000.cmd.sh b/flossing_suite/results/toy_rnn/toy_baseline_no_floss_N80_k40_E1000.cmd.sh
new file mode 100755
index 0000000..d7d9526
--- /dev/null
+++ b/flossing_suite/results/toy_rnn/toy_baseline_no_floss_N80_k40_E1000.cmd.sh
@@ -0,0 +1,43 @@
+#!/usr/bin/env bash
+set -euo pipefail
+cd "/home/yurenh2/rrm"
+export CUDA_VISIBLE_DEVICES="0"
+export PYTHONUNBUFFERED=1
+exec "/home/yurenh2/miniconda3/envs/rrm/bin/python" research/flossing/engelken_python_flossing.py \
+ --hidden-size 80 \
+ --n-lyap 40 \
+ --train-epochs 1000 \
+ --inter-period 100 \
+ --inter-epochs 100 \
+ --batch-size 16 \
+ --input-dim 1 \
+ --train-steps 300 \
+ --lyap-steps 55 \
+ --floss-input-steps 300 \
+ --seed-ic 1 \
+ --seed-input 1 \
+ --seed-net 1 \
+ --seed-ons 1 \
+ --lr 0.001 \
+ --beta1 0.9 \
+ --beta2 0.999 \
+ --init-type 1 \
+ --recurrent-gain 1.0 \
+ --recurrent-mean-gain 0.0 \
+ --input-scale 1.0 \
+ --delay 10 \
+ --ws-std 1.0 \
+ --ws-mean 0.0 \
+ --wr-std 1.0 \
+ --wr-mean 0.0 \
+ --b-std 0.1 \
+ --b-mean 0.0 \
+ --task -1 \
+ --lyap-target 0.0 \
+ --eval-every 100 \
+ --eval-batches 4 \
+ --log-every-floss 25 \
+ --device cuda \
+ --pre-epochs "0" \
+ --max-inter-episodes "0" \
+ --out "/home/yurenh2/rrm/research/flossing/flossing_suite/results/toy_rnn/toy_baseline_no_floss_N80_k40_E1000.json"
diff --git a/flossing_suite/results/toy_rnn/toy_pre_inter_N80_k40_E1000.cmd.sh b/flossing_suite/results/toy_rnn/toy_pre_inter_N80_k40_E1000.cmd.sh
new file mode 100755
index 0000000..13383f9
--- /dev/null
+++ b/flossing_suite/results/toy_rnn/toy_pre_inter_N80_k40_E1000.cmd.sh
@@ -0,0 +1,43 @@
+#!/usr/bin/env bash
+set -euo pipefail
+cd "/home/yurenh2/rrm"
+export CUDA_VISIBLE_DEVICES="3"
+export PYTHONUNBUFFERED=1
+exec "/home/yurenh2/miniconda3/envs/rrm/bin/python" research/flossing/engelken_python_flossing.py \
+ --hidden-size 80 \
+ --n-lyap 40 \
+ --train-epochs 1000 \
+ --inter-period 100 \
+ --inter-epochs 100 \
+ --batch-size 16 \
+ --input-dim 1 \
+ --train-steps 300 \
+ --lyap-steps 55 \
+ --floss-input-steps 300 \
+ --seed-ic 1 \
+ --seed-input 1 \
+ --seed-net 1 \
+ --seed-ons 1 \
+ --lr 0.001 \
+ --beta1 0.9 \
+ --beta2 0.999 \
+ --init-type 1 \
+ --recurrent-gain 1.0 \
+ --recurrent-mean-gain 0.0 \
+ --input-scale 1.0 \
+ --delay 10 \
+ --ws-std 1.0 \
+ --ws-mean 0.0 \
+ --wr-std 1.0 \
+ --wr-mean 0.0 \
+ --b-std 0.1 \
+ --b-mean 0.0 \
+ --task -1 \
+ --lyap-target 0.0 \
+ --eval-every 100 \
+ --eval-batches 4 \
+ --log-every-floss 25 \
+ --device cuda \
+ --pre-epochs "100" \
+ --max-inter-episodes "2" \
+ --out "/home/yurenh2/rrm/research/flossing/flossing_suite/results/toy_rnn/toy_pre_inter_N80_k40_E1000.json"
diff --git a/flossing_suite/results/toy_rnn/toy_prefloss_N80_k40_E1000.cmd.sh b/flossing_suite/results/toy_rnn/toy_prefloss_N80_k40_E1000.cmd.sh
new file mode 100755
index 0000000..db82a74
--- /dev/null
+++ b/flossing_suite/results/toy_rnn/toy_prefloss_N80_k40_E1000.cmd.sh
@@ -0,0 +1,43 @@
+#!/usr/bin/env bash
+set -euo pipefail
+cd "/home/yurenh2/rrm"
+export CUDA_VISIBLE_DEVICES="1"
+export PYTHONUNBUFFERED=1
+exec "/home/yurenh2/miniconda3/envs/rrm/bin/python" research/flossing/engelken_python_flossing.py \
+ --hidden-size 80 \
+ --n-lyap 40 \
+ --train-epochs 1000 \
+ --inter-period 100 \
+ --inter-epochs 100 \
+ --batch-size 16 \
+ --input-dim 1 \
+ --train-steps 300 \
+ --lyap-steps 55 \
+ --floss-input-steps 300 \
+ --seed-ic 1 \
+ --seed-input 1 \
+ --seed-net 1 \
+ --seed-ons 1 \
+ --lr 0.001 \
+ --beta1 0.9 \
+ --beta2 0.999 \
+ --init-type 1 \
+ --recurrent-gain 1.0 \
+ --recurrent-mean-gain 0.0 \
+ --input-scale 1.0 \
+ --delay 10 \
+ --ws-std 1.0 \
+ --ws-mean 0.0 \
+ --wr-std 1.0 \
+ --wr-mean 0.0 \
+ --b-std 0.1 \
+ --b-mean 0.0 \
+ --task -1 \
+ --lyap-target 0.0 \
+ --eval-every 100 \
+ --eval-batches 4 \
+ --log-every-floss 25 \
+ --device cuda \
+ --pre-epochs "100" \
+ --max-inter-episodes "0" \
+ --out "/home/yurenh2/rrm/research/flossing/flossing_suite/results/toy_rnn/toy_prefloss_N80_k40_E1000.json"