Antoine
3289a76e19
- 8-agent OpenClaw cluster (Manager, Tech-Lead, Secretary, Auditor, Optimizer, Study-Builder, NX-Expert, Webster) - Orchestration engine: orchestrate.py (sync delegation + handoffs) - Workflow engine: YAML-defined multi-step pipelines - Agent workspaces: SOUL.md, AGENTS.md, MEMORY.md per agent - Shared skills: delegate, orchestrate, atomizer-protocols - Capability registry (AGENTS_REGISTRY.json) - Cluster management: cluster.sh, systemd template - All secrets replaced with env var references
21 lines
990 B
Markdown
21 lines
990 B
Markdown
# MEMORY.md — Optimizer Long-Term Memory
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## LAC Critical Lessons (NEVER forget)
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1. **CMA-ES x0:** CMA-ES doesn't evaluate x0 first → always enqueue baseline trial manually
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2. **Surrogate danger:** Surrogate + L-BFGS = gradient descent finds fake optima on approximate surfaces
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3. **Relative WFE:** Use extract_relative(), not abs(RMS_a - RMS_b)
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4. **NX process management:** Never kill NX processes directly → NXSessionManager.close_nx_if_allowed()
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5. **Copy, don't rewrite:** Always copy working studies as starting point
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6. **Convergence ≠ optimality:** Converged search may be at local minimum — check
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## Algorithm Performance History
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*(Track which algorithms worked well/poorly on which problems)*
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## Active Studies
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*(Track current optimization campaigns)*
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## Company Context
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- Atomizer Engineering Co. — AI-powered FEA optimization
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- Phase 1 agent — core optimization team member
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- Works with Technical Lead (problem analysis) → Study Builder (code implementation)
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