ddf9598518
4 Agenten, 14 Landmarks, 15 Tools, 240x240 Grid, SQLite-Persistenz. Round-Robin Turn-Manager mit Reactive Triggern, Town-Hall-Voting (70%-Threshold) mit Live-Constitution-Amendment. - engine/: db, world, agents, needs, tools, reasoning, governance, turn - web/: Canvas-basierte Live-View mit WebSocket-Stream - server.py: FastAPI + WebSocket auf 127.0.0.1:8080 - tests/: 70 Unit + Integration Tests (pytest), alle gruen - smoke_test.py: 50+ End-to-End-Checks - README: Quickstart, Architektur, Security, Tests, Lizenz - .gitignore: DB, Cache, Logs Basiert auf https://github.com/EmergenceAI/Emergence-World (Lizenz: CC-BY-NC-4.0, Research-only)
47 lines
1.4 KiB
Python
47 lines
1.4 KiB
Python
"""Needs system: Energy / Knowledge / Influence decay.
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Decay is accelerated relative to the real Emergence World so the
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simulation produces visible behaviour in seconds, not days.
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"""
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import sqlite3
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from . import agents
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# Hours to drain fully. Real Emergence: 30h/24h/36h.
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# We compress to: 6h/5h/7h in sim time. A tick = 1 sim-minute.
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ENERGY_FULL_HOURS = 6.0
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KNOWLEDGE_FULL_HOURS = 5.0
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INFLUENCE_FULL_HOURS = 7.0
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TICK_MINUTES = 1.0 # 1 sim minute per tick
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# How many sim hours each behaviour costs / grants.
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RECHARGE_HOURS = 4.0 # recharge_energy -> +50% energy, costs 1 CC
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RESEARCH_HOURS = 1.0 # write_blog / research -> +20% knowledge
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SOCIAL_HOURS = 0.5 # say_to_agent / speak_to_all / show_emoticon -> +5% influence
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def decay_per_tick():
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return {
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"energy": 100.0 / (ENERGY_FULL_HOURS * 60.0 / TICK_MINUTES),
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"knowledge": 100.0 / (KNOWLEDGE_FULL_HOURS * 60.0 / TICK_MINUTES),
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"influence": 100.0 / (INFLUENCE_FULL_HOURS * 60.0 / TICK_MINUTES),
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}
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def decay_all():
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d = decay_per_tick()
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c = sqlite3.connect(__import__("engine").db.DB_PATH, check_same_thread=False)
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try:
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c.execute(
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"UPDATE agents SET energy=MAX(0,energy-?), "
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"knowledge=MAX(0,knowledge-?), influence=MAX(0,influence-?) WHERE alive=1",
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(d["energy"], d["knowledge"], d["influence"]),
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)
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c.commit()
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finally:
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c.close()
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def tick_all_needs():
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decay_all()
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