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{"type":"item.completed","item":{"id":"item_1","type":"agent_message","text":"```python\nimport json, numpy as np\nsource=open(\"/work/policy_design_v7.py\").read()\npatch=r'''\n    # Defend vulnerable groups before their final liberty is taken.\n    # The feature is graded: strongest in atari, weaker with nearby\n    # evidence of additional liberties.\n    for p in range(81):\n        j=u(2,p)\n        W[3][:,j]=0\n        B[3][j]=0\n        W[3][u(0,p),j]=3\n        W[3][u(2,p),j]=-1\n        for q in adj[p]:\n            W[3][u(2,q),j]-=0.5\n        W[4][u(4,p),u(4,p)]=-12\n'''\nsource=source.replace('    OW *= cfg[\"temperature_scale\"]',\n                      patch+'\\n    OW *= cfg[\"temperature_scale\"]')\nopen(\"/work/policy_design_v10.py\",\"w\").write(source)\nopen(\"/work/policy_design.py\",\"w\").write(source)\ncfg=json.load(open(\"/work/policy_config.json\"))\ncfg.update(rescue=2.2,opening_center=0.0)\nns={}\nexec(compile(source,\"/work/policy_design.py\",\"exec\"),ns)\ncfg,tensors=ns[\"build\"](save,cfg)\njson.dump(cfg,open(\"/work/policy_config.json\",\"w\"),indent=2)\nnp.savez(\"/work/policy_v10.npz\",**tensors)\nprint(\"Saved v10: graded preventive defense, with suicidal rescues still suppressed.\")\n```"}}
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