Phase 0.5 — closed-loop agent ↔ simulator

The question: can an agent run a full task against the learned simulator instead of a Docker container — coherently and cheaply?

The unblock: (b) full-transcript 1M is a policy and a world model in one network (assistant turns = commands, user turns = observations). So a single vLLM plays both roles, alternating turn by turn — no two-process coordination (the TPU_VISIBLE_CHIPS issue that stalled the earlier attempt). One v6e-4, 20 held-out tasks, up to 50 turns each (closed_loop_selfplay.py).

Results (20 episodes, 910 simulated turns — measured, not projected)

metric	value
mean turns survived	45.8 / 50
simulator latency	0.74 s/turn
per-turn total (agent + sim)	1.45 s
catastrophic sim degeneration (runaway loop)	1.76% (16 / 910 turns)
any noticeable sim repetition (broader)	5.9% (54 / 910)
episodes where the agent repeats a command ≥3×	19 / 20
clean termination (submit marker; no graded patch)	5 / 20
episodes issuing ≥1 real edit command (`sed -i`/heredoc/`tee`)	11 / 20 (98 cmds)
episodes producing an actual diff / patch	0 / 20

The loop self-stabilizes against catastrophic loops. Runaway degeneration is 1.76% here vs 13% for the same checkpoint in single-shot free sampling — conditioning each observation on a coherent trajectory prefix keeps the model on the rails. With (b) 1M + the degeneration fixes (max_tokens=512, repetition penalty, thinking off), it holds for full 50-turn episodes. Milder repetition persists, though (see breakdown below) — “self-stabilizes” is about page-out blow-ups, not all repetition.
The simulator is cheap — 0.74 s/turn, ~1.5 s per full turn, well under a Daytona round-trip, and it removes Daytona’s 100-instance cap (the sim is just another TPU).
“Termination” is not a real patch. All 5/20 clean terminations ended with the agent emitting the submit marker (echo COMPLETE_TASK_AND_SUBMIT_FINAL_OUTPUT), and 11/20 episodes issued genuine edit commands (sed -i, cat <<EOF, tee — 98 in total). But no episode produced an actual diff/patch (0/20): with no real filesystem behind the loop, those edits were never applied — the simulator just emitted plausible success (google/swift-benchmark ep: “All changes applied successfully!”). One of the 5 submitting episodes (lucasbento/create-graphql) made zero edits and declared done on changes it had only described. A clean termination here means the agent believed it finished, not that a verifiable fix exists.

Honest limit: a fully-simulated rollout has no ground-truth pass/fail — finding 3 is the concrete face of it: the agent “submits,” the sim rubber-stamps, and nothing is graded. If the sim writes the test output, “tests passed” is a hallucination. This validates coherence and cost, not pass@1. The payoff number needs the next experiment: SFT an agent on sim-generated rollouts, then eval on the real container — sim replaces the env during data generation, grading stays real.

What the repetition actually looks like

The headline 1.76% is the catastrophic rate — a simulator turn that runs > 800 chars and is almost pure repetition (zlib ratio < 0.08), the unusable page-out loop. Loosening to any human-noticeable repetition (≥ 3 identical lines, a 2–6-line block repeated ≥ 3×, an incrementing counter, or > 40% duplicate lines) lifts it to 5.9% (54 / 910) — still ~5× rarer than the 13%+ of unconditioned free sampling, because each observation is anchored to a real trajectory prefix. The 54 split into the same three mechanical kinds as free sampling:

kind	count	example
exact-line loop (a line echoed ≥ 3×)	33	`.assertIn(...)` repeated
block loop (a 2–6-line block repeated)	13	a stanza of file output looped
incrementing counter	8	`analysis_module_2, _3, _4, …`

But the repetition you actually notice browsing is mostly agent-side, not simulator-side: only 1.5% of agent turns are internally repetitive, yet in 19 / 20 episodes the policy re-issues the same command ≥ 3× — the read-heavy, grep-on-repeat behavior from Phase 0 (“47 greps, 0 seds”), now playing out against the learned env. So two distinct loops coexist: a rare simulator loop (well controlled) and a pervasive agent command-loop (a policy habit the simulator faithfully mirrors back).

Browse real rollouts

The same (b) 1M network is both agent and simulator; agent turns are amber, simulator observations blue. Repeating observations are flagged — orange for noticeable loops (e.g. a line echoed ×9), red for a runaway page-out. This catches the milder 5.9%-class repetition, not just the catastrophic 1.76%.

google/swift-benchmark · 22 turns · clean termination ✓ · no degenerate sim turns · showing first 30 of 43 turns

▸ agent (command) · turn 1 · 357 chars

THOUGHT: First, I need to understand the repository structure to locate the relevant files mentioned in the issue. The issue mentions `Sources/Benchmark/BenchmarkSetting.swift` which suggests there's a Swift project with a benchmark module. Let me explore the repository structure to find these files.

```bash
find . -type f -name "*.swift" | head -20
```

◂ simulator (observation) · turn 1 · 415 chars

Observation: ./Package.swift
./Sources/Benchmark/BenchmarkCoW.swift
./Sources/Benchmark/BenchmarkDelay.swift
./Sources/Benchmark/BenchmarkMap.swift
./Sources/Benchmark/BenchmarkReduce.swift
./Sources/Benchmark/BenchmarkSet.swift
./Sources/Benchmark/BenchmarkSlice.swift
./Sources/Benchmark/BenchmarkFilter.swift
./Sources/Benchmark/BenchmarkLaziness.swift
./Sources/Benchmark/main.swift
./Sources/Utils/Utils.swift

▸ agent (command) · turn 2 · 305 chars

THOUGHT: I can see there are several Swift files in the Sources/Benchmark directory. The issue specifically mentions `BenchmarkSetting.swift` which I need to find. Let me look more carefully at the directory structure and search for the exact file name.

```bash
find . -name "BenchmarkSetting.swift"
```

◂ simulator (observation) · turn 2 · 56 chars

Observation: ./Sources/Benchmark/BenchmarkSetting.swift

▸ agent (command) · turn 3 · 313 chars

THOUGHT: Great! I found the file mentioned in the issue. Now let me examine its contents to understand the current implementation of the warmupIterations method and how it handles the precedence and validation issues described in the problem statement.

```bash
cat ./Sources/Benchmark/BenchmarkSetting.swift
```

◂ simulator (observation) · turn 3 · 2,201 chars

Observation: // Copyright 2020 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// S

▸ agent (command) · turn 4 · 726 chars

THOUGHT: Now I can see the current implementation. Looking at the code, I can identify the issues mentioned in the problem description:

1. The `warmupIterations` field is stored as `Int?` (optional) but the `numberOfWarmupIterations` property returns `Int` (non-optional) - this means it's not properly handling the case where warmup iterations is 0.
2. The precedence order is not correctly implemented - the CLI values should take precedence over other defaults/settings.
3. The validation logic n

◂ simulator (observation) · turn 4 · ⚠ repeated line ×9 · 776 chars

Observation: ./Package.swift:  .benchmark(name: "BenchmarkWarmupIterations", config: BenchmarkWarmupIterationsConfigurator()) {
./Sources/Benchmark/BenchmarkSetting.swift:  let warmupIterations: Int?
./Sources/Benchmark/BenchmarkSetting.swift:  let warmupIterations: Int?
./Sources/Benchmark/BenchmarkSetting.swift:  let warmupIterations: Int?
./Sources/Benchmark/BenchmarkSetting.swift:  let warmupIterations: Int?
./Sources/Benchmark/BenchmarkSetting.swift:  let warmupIterations: Int?
./Sources/Be

▸ agent (command) · turn 5 · 241 chars

THOUGHT: Let me also check the main benchmark runner to understand how the CLI arguments are processed and how they should override the settings:

```bash
find . -name "*.swift" -exec grep -l "warmup.*iterations\|WarmupIterations" {} \;
```

◂ simulator (observation) · turn 5 · 131 chars

Observation: ./Package.swift
./Sources/Benchmark/BenchmarkSetting.swift
./Sources/Benchmark/main.swift
./Sources/Utils/Utils.swift

▸ agent (command) · turn 6 · 141 chars

THOUGHT: Let me examine the main benchmark file to understand how CLI arguments are handled:

```bash
cat ./Sources/Benchmark/main.swift
```

◂ simulator (observation) · turn 6 · 2,021 chars

Observation: // Copyright 2020 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// S

▸ agent (command) · turn 7 · 748 chars

THOUGHT: Now I understand the structure better. Looking at the main.swift file, I can see that `warmupIterations` is defined as an option with default value 10, and the CLI arguments should override this. 

Looking at the current `BenchmarkSettings` implementation in `BenchmarkSetting.swift`, I need to:

1. Fix the precedence so CLI arguments take priority over other defaults/settings
2. Make sure `warmupIterations` is always non-optional (returns 0 when not set)
3. Update validation to allow ze

◂ simulator (observation) · turn 7 · 13 chars

Observation:

▸ agent (command) · turn 8 · 152 chars

THOUGHT: Let me check what tests exist for the benchmark functionality:

```bash
find . -name "*test*" -type f -o -name "*Test*" -type f | head -10
```

◂ simulator (observation) · turn 8 · 61 chars

Observation: ./Package.swift
./Sources/Utils/UtilsTest.swift

▸ agent (command) · turn 9 · 131 chars

THOUGHT: Let me look at the test file to understand the expected behavior better:

```bash
cat ./Sources/Utils/UtilsTest.swift
```

◂ simulator (observation) · turn 9 · 1,997 chars

Observation: // Copyright 2020 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// S

▸ agent (command) · turn 10 · 8,993 chars

THOUGHT: Now I understand the issue clearly. Looking at the current implementation in `BenchmarkSetting.swift`, I need to:

1. Fix the `warmupIterations` field to be non-optional (default 0 when not set)
2. Update the `numberOfWarmupIterations` property to always return a non-optional integer
3. Update the validation logic to allow zero warmup iterations
4. Modify the benchmark execution logic to handle zero warmup iterations properly

Let me make the necessary changes to the `BenchmarkSetting.s

◂ simulator (observation) · turn 10 · 61 chars

Please always provide EXACTLY ONE action in triple backticks.

▸ agent (command) · turn 11 · 317 chars

THOUGHT: I see that my previous sed command was too complex and caused issues. Let me approach this more systematically by examining the exact current state of the file and making precise changes.

First, let me check the exact current content of the file:

```bash
cat ./Sources/Benchmark/BenchmarkSetting.swift
```

◂ simulator (observation) · turn 11 · 2,200 chars

Observation: // Copyright 2020 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// S

▸ agent (command) · turn 12 · 2,502 chars

THOUGHT: Now I can see the exact structure. I need to make three key changes:

1. Change `let warmupIterations: Int?` to `let warmupIterations: Int = 0` 
2. Change the `numberOfWarmupIterations` property to always return a non-optional integer
3. Update the validation logic to allow zero warmup iterations

Let me make these changes step by step:

```bash
# First, change the type annotation and initialization
sed -i 's/let warmupIterations: Int?/let warmupIterations: Int = 0/' ./Sources/Benchmark

◂ simulator (observation) · turn 12 · 61 chars

Please always provide EXACTLY ONE action in triple backticks.

▸ agent (command) · turn 13 · 2,533 chars

THOUGHT: My sed command is getting too complex and causing issues. Let me take a different approach. I'll rewrite the entire file with the correct implementation based on the requirements. First, let me backup the original file and then create a corrected version.

```bash
cp ./Sources/Benchmark/BenchmarkSetting.swift ./Sources/Benchmark/BenchmarkSetting.swift.backup && \
cat > ./Sources/Benchmark/BenchmarkSetting.swift << 'EOF'
// Copyright 2020 Google LLC
//
// Licensed under the Apache Licens

◂ simulator (observation) · turn 13 · 61 chars

Please always provide EXACTLY ONE action in triple backticks.

▸ agent (command) · turn 14 · 450 chars

THOUGHT: I see that my replacement didn't work correctly. Let me check what happened and do this properly. I need to be more careful with the sed commands and make sure I'm replacing the right parts correctly. Let me first see the exact current content again and then make precise replacements.

```bash
# Let me check the exact content around the problematic area
grep -n -A 10 -B 5 "warmupIterations" ./Sources/Benchmark/BenchmarkSetting.swift
```

◂ simulator (observation) · turn 14 · 1,158 chars

Observation: 18-protocol BenchmarkConfigurator {
19-  func configure(benchmark: Benchmark) -> BenchmarkSettings
20-}
21-
22-struct BenchmarkSettings: Decodable, Hashable {
23:  let group: String
24-  let name: String
25:  let warmupIterations: Int?
26-  let iterations: Int
27-
28-  private let _settings: [String] = [
29-    "group",
30-    "name",
31-    "warmupIterations",
32-    "iterations",
33-  ]
34-
35-  required init?(json: [String: Any]) {
--
49-    self.iterations = decodedIterations
50

▸ agent (command) · turn 15 · 1,201 chars

THOUGHT: Now I can see the exact structure. I need to:
1. Change `let warmupIterations: Int?` to `let warmupIterations: Int = 0`
2. Change the `numberOfWarmupIterations` property to always return a non-optional integer
3. Update the validation logic to allow zero warmup iterations

Let me do this properly with sed commands:

```bash
# Change the type annotation and initialization
sed -i '25s/let warmupIterations: Int?/let warmupIterations: Int = 0/' ./Sources/Benchmark/BenchmarkSetting.swift &&

◂ simulator (observation) · turn 15 · 13 chars

Observation:

Agent and simulator are the same (b) 1M network playing both roles. Click expand to see a full observation. Complete transcripts at gs://marin-us-east5/closed-loop/b1m-selfplay-2/.

How we got here (superseded notes)

Pre-run probes and the dropped dedicated simulator

Batch-shrinkage (free probe): counting active arm-(a) trajectories per turn showed 84% run to max_turns=50 (the 10K agent rarely clean-terminates), so the active batch never drops below ~quarter-full — batch shrinkage isn’t a real cost at this scale. Confirmed in the run above (5/20 clean-terminate).

Latency sweep & the three pathologies: an earlier characterization used the dedicated env-rewritten simulator (since dropped as not apples-to-apples) and surfaced three failure modes — output-length loops, no-EOS runaway, and Qwen <think>-mode leakage at long context. All three are addressed by the sim-turn fixes used above (max_tokens=512, repetition penalty, enable_thinking=false), which is why the closed-loop degeneration is only 1.76%.

Per-turn budget projection: pre-run estimate was ~5–9 s/turn; the measured 1.45 s beat it. The earlier dual-vLLM attempt failed (TPU_VISIBLE_CHIPS not honored); the single-model self-play above sidesteps it entirely.

Reproduce

scripts/closed_loop_selfplay.py on a single v6e-4 (us-east5); simulator = (b) 1M …_1m_8192tokens_arch32k_echo_v5p32-a2b7ba/hf/step-15624. Output (per-episode files, heartbeat, transcripts): gs://marin-us-east5/closed-loop/b1m-selfplay-2/.

Simulator samples Evaluation methods