arXiv AI

The Theory of Strategic Evolution: Games with Endogenous Players and Strategic Replicators

arXiv:2512. 07901v3 Announce Type: replace-cross Abstract: Von Neumann founded both game theory and the theory of self-reproducing automata, but the two programs never merged.

arXiv AI
Sep 12

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

The paper introduces Autopoietic Game Theory, a computational model where social interactions, replication mechanisms, and computational costs co-evolve within a substrate of randomly initialized Z80 machine code programs. By embedding a social dilemma directly into the physics of computation, the authors demonstrate that scarcity of resources can make defection self-limiting, leading to the emergence of self-replicating, cooperative strategies. Empirical results show evolved programs suppress stealing, and spatial assortment enhances structural complexity and task performance, while the framework can also incorporate exogenous pressures such as math tasks tied to computation budgets.

By Kunal Jha, Francesco Cicala, Blaise Ag\"uera y Arcas, Blake Aaron Richards, Natasha Jaques, Max Kleiman-Weiner, Eyvind Niklasson
arXiv AI
Aug 7

From Economic Agents to Agentic Economies: A Systems Blueprint for Economic World Models

arXiv:2608. 06020v1 Announce Type: new Abstract: Economic World Models (EWMs) are generative economic models that simulate how economies evolve from within by modeling heterogeneous agents, their beliefs and actions, and the market and institutional mechanisms through which their interactions produce aggregate outcomes.

By Jiale Han, Xiang Li, Jing Qian, Wenyuan Gu, Pin Gao, Ye Luo, Hongyuan Zha, Dacheng Tao, Benyou Wang, Lin William Cong
arXiv AI
Jul 7

Serious Games: Human-AI Interaction, Evolution, and Coevolution

arXiv:2505. 16388v2 Announce Type: replace Abstract: The serious games between humans and AI have only just begun.

By Nandini Doreswamy (Southern Cross University, Lismore, New South Wales, Australia, National Coalition of Independent Scholars), Louise Horstmanshof (Southern Cross University, Lismore, New South Wales, Australia)
arXiv AI
Jun 9

Payoff scaling shapes cooperation in LLM agents across languages

arXiv:2601. 19082v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed as autonomous agents that negotiate, coordinate, and act on behalf of users.

By Trung-Kiet Huynh, Dao-Sy Duy-Minh, Thanh-Bang Cao, Phong-Hao Le, Hong-Dan Nguyen, Phu-Quy Nguyen-Lam, Minh-Luan Nguyen-Vo, Hong-Phat Pham, Phu-Hoa Pham, Thien-Kim Than, Chi-Nguyen Tran, Huy Tran, Gia-Thoai Tran-Le, Alessio Buscemi, Le Hong Trang, The Anh Han
arXiv AI
Sep 12

Role differentiation as ignition of a collective information engine: Structuration in Agent Populations

The paper proposes a new framework for collective information engines that rely on role differentiation rather than consensus. By modeling anti‑coordination games, agents infer roles from noisy social signals tied to persistent identities, and role‑following actions reinforce those identities, creating a feedback loop that can drive collective order. The authors show that when a social loop gain—determined by identity persistence, cognitive capacity, channel fidelity, and schema strength—exceeds one, roles emerge in a bifurcation cascade whose type is selected by resource‑driven replicator dynamics, offering a mechanistic basis for distributional AGI takeoff and a control lever for platform design.

By Maximilian Puelma Touzel