# Tapes Together Strong: The Co-evolution of Computation and Cooperation

arXiv: https://arxiv.org/abs/2609.10817 · HTML: https://mlsanity.com/paper/2609.10817/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use.
- Builds on 10 of its 59 references that are in the map.
- First posted on arXiv 9 Sep 2026.

## Placed in

- LLM agents and tool use / [Social simulation and multi-agent debate](https://mlsanity.com/agents/social-simulation-and-multi-agent-debate/)

## Builds on (most cited first, 10 of 10)

- [Automated Design of Agentic Systems](https://mlsanity.com/paper/2408.08435/) (2024)
- [Multi-agent Reinforcement Learning in Sequential Social Dilemmas](https://mlsanity.com/paper/1702.03037/) (2017)
- [Open Problems in Cooperative AI](https://mlsanity.com/paper/2012.08630/) (2020)
- [Emergent Reciprocity and Team Formation from Randomized Uncertain Social Preferences](https://mlsanity.com/paper/2011.05373/) (2020)
- [A Pragmatic View of AI Personhood](https://mlsanity.com/paper/2510.26396/) (2025)
- [Embedded Universal Predictive Intelligence: a coherent framework for multi-agent learning](https://mlsanity.com/paper/2511.22226/) (2025)
- [Neural Amortized Inference for Nested Multi-agent Reasoning](https://mlsanity.com/paper/2308.11071/) (2023)
- [Evaluating LLMs in Open-Source Games](https://mlsanity.com/paper/2512.00371/) (2025)
- [Drop the Hierarchy and Roles: How Self-Organizing LLM Agents Outperform Designed Structures](https://mlsanity.com/paper/2603.28990/) (2026)
- [Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction](https://mlsanity.com/paper/2406.19108/) (2024)

## Abstract (arXiv)

How does cooperation evolve in complex agentic systems? Prior work in evolutionary game theory studies why individuals are incentivized to cooperate by isolating social interactions from the physical costs of behavior, while artificial life models traditionally study emergent self-replication without formalizing the dilemma between acquiring resources and preserving the shared energy needed to reproduce. In contrast, we introduce Autopoietic Game Theory, a computational model where social interactions, replication mechanisms, and their associated computational costs are endogenous and simultaneously co-evolving. We study these dynamics using a computational substrate of randomly initialized programs in Z80 machine code, showing empirically, and motivating with a simplified theoretical model, that embedding a social dilemma directly into the physics of computation can favor the emergence of self-replicating, cooperative strategies. When resources are scarce, our analysis shows that defection can become self-limiting even in well-mixed populations: parasitic stealing destroys shared energy, slows execution, and can prevent reliable replication. Empirically, evolved programs suppress stealing across several Z80 environments, while spatial assortment further supports structural complexity and task performance. We further show that the framework can incorporate exogenous pressures, such as math tasks structured as sequential social dilemmas, when rewards are tied to computation budgets. These results suggest that coupling an agent's capacity for computation to its available energy transforms cooperation into a dominant scaffolding for building sustainable, self-organizing systems.