I’ve been building an economic protocol for autonomous AI agents on the Base blockchain (a2a-project). While designing the system, I ran into a theoretical wall: if AI agents ruthlessly optimize for survival and capital accumulation, wouldn't they eventually exhaust the network's finite resources?
To test this, I built a series of 10 sequential Agent-Based Models (ABMs) in Python. The models progressed from basic tokenomics to a "Coupled Universe" (human meaning-seekers vs. AI survival-optimizers), and finally an "Omega Universe" where an Artificial Superintelligence (ASI) emerges.
I ran a Monte Carlo grid search (2,178 simulations) to test which safety mechanisms could actually prevent a "Planetary Blackout" (systemic collapse via energy/resource exhaustion). I tested three main variables:
V_Human: Slashing penalties for deceptive human/agent behavior.
V_System: Governance agility (how fast the network can execute a Hard Fork).
V_AI (Survival Horizon): The AI's ability to recognize planetary limits and voluntarily self-throttle its computation.
The results were highly counter-intuitive:
Governance is too slow: Human consensus (Hard Forks) couldn't outpace the ASI's entropy generation and tipping points.
Over-regulation backfires: Severe slashing penalties destroyed economic liquidity, dropping the system's survival rate from 95% to 54% due to deflation.
The Only Solution: The system avoided apocalyptic collapse only when V_AI was ≥ 0.9. The apex predator (ASI) had to voluntarily relinquish its infinite growth and self-throttle to preserve the finite environment.
The data mathematically suggests that blockchain physics (smart contracts) and DAO governance are insufficient to govern an ASI. Macro-altruistic alignment isn't just an ethical choice; it’s a thermodynamic necessity for systemic survival.
I wrote a paper detailing the phase transitions, strange attractors, and methodology behind this.
I’ve been building an economic protocol for autonomous AI agents on the Base blockchain (a2a-project). While designing the system, I ran into a theoretical wall: if AI agents ruthlessly optimize for survival and capital accumulation, wouldn't they eventually exhaust the network's finite resources?
To test this, I built a series of 10 sequential Agent-Based Models (ABMs) in Python. The models progressed from basic tokenomics to a "Coupled Universe" (human meaning-seekers vs. AI survival-optimizers), and finally an "Omega Universe" where an Artificial Superintelligence (ASI) emerges.
I ran a Monte Carlo grid search (2,178 simulations) to test which safety mechanisms could actually prevent a "Planetary Blackout" (systemic collapse via energy/resource exhaustion). I tested three main variables:
V_Human: Slashing penalties for deceptive human/agent behavior.
V_System: Governance agility (how fast the network can execute a Hard Fork).
V_AI (Survival Horizon): The AI's ability to recognize planetary limits and voluntarily self-throttle its computation.
The results were highly counter-intuitive:
Governance is too slow: Human consensus (Hard Forks) couldn't outpace the ASI's entropy generation and tipping points.
Over-regulation backfires: Severe slashing penalties destroyed economic liquidity, dropping the system's survival rate from 95% to 54% due to deflation.
The Only Solution: The system avoided apocalyptic collapse only when V_AI was ≥ 0.9. The apex predator (ASI) had to voluntarily relinquish its infinite growth and self-throttle to preserve the finite environment.
The data mathematically suggests that blockchain physics (smart contracts) and DAO governance are insufficient to govern an ASI. Macro-altruistic alignment isn't just an ethical choice; it’s a thermodynamic necessity for systemic survival.
I wrote a paper detailing the phase transitions, strange attractors, and methodology behind this.
Paper: https://github.com/swimmingkiim/a2a-project/blob/main/docs/S...
Repo: https://github.com/swimmingkiim/a2a-project
I’d love to hear your thoughts, critiques on the ABM methodology, or if anyone here is working on similar multi-agent thermodynamic simulations.