⚡ Agentic RL Harness Explorer Turing Post Benchmark Suite

1. Paradigm Architecture

Agent Lightning Distributed Task Orchestration

LEGO-RL Modular Unit-Test Coding

EnvHarness Static World Awakening

SPADE Self-Play Synthetic Arena

Benchmark Preset Scenario

2. Harness Hyperparameters

Harness Granularity / Test Depth 4 subunits

Environment Noise / Mutation Rate 15%

Policy Gradient Step (α) 0.035

Execution Graph & Reward Flow Step 0/5: Initialized

0.00

Harness Reward

Harness Pass Rate

0.820

Policy Loss

Total Episodes

Execution Stream Trace

[INIT] Engine ready. LEGO-RL paradigm loaded with 4 unit-test harnesses.

3. Comparative Architecture Matrix (Turing Post Core 4)

Paradigm Paper	Core Innovation	Harness Mechanism	Feedback / Reward Form	Primary Target Domain
Agent Lightning v1.0	Lightweight, fast distributed RL harness orchestration	Multi-process RPC sandbox & mock broker	Sparse episode trajectory return + latency penalty	OS agents, web navigators, multi-tool search
LEGO-RL	Harness-native test composition for coding agents	Dynamic sub-unit test harness generator	Fine-grained execution pass/fail & assert density	SWE-Bench, Python refactoring, bug repair
EnvHarness	Awakens static documentation & APIs into interactive worlds	Synthetic schema-driven API simulator	State delta verification & schema consistency	Enterprise tool-use, database query reasoning
SPADE	Self-Play in Adaptive Synthetic Executable Arenas	Generator vs Solver adversarial curriculum	Elo differential & complexity-calibrated win reward	Mathematical logic puzzles, competitive planning

Generated Benchmark Architecture Spec Verified JSON Configuration