Incentivized Symbiosis: A Paradigm for Human-Agent Coevolution
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Abstract (arXiv)
Cooperation is vital to our survival and progress. Evolutionary game theory offers a lens to understand the structures and incentives that enable cooperation to be a successful strategy. As artificial intelligence agents become integral to human systems, the dynamics of cooperation take on unprecedented significance. The convergence of human-agent teaming, contract theory, and decentralized frameworks like Web3, grounded in transparency, accountability, and trust, offers a foundation for fostering cooperation by establishing enforceable rules and incentives for humans and AI agents. We conceptualize Incentivized Symbiosis as a social contract between humans and AI, inspired by Web3 principles and encoded in blockchain technology, to define and enforce rules, incentives, and consequences for both parties. By exploring this paradigm, we aim to catalyze new research at the intersection of systems thinking in AI, Web3, and society, fostering innovative pathways for cooperative human-agent coevolution.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 3 of its 8 references that are in the map. First posted on arXiv 8 Dec 2024.
Builds on
3 of 8 references.
References · 3
- 2023When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directionscited by 84
- 2024Collaborative Mean Estimation Among Heterogeneous Strategic Agents: Individual Rationality, Fairness, and Truthful Contributioncited by 4
- 2024Redefining Accountability: Navigating Legal Challenges of Participant Liability in Decentralized Autonomous Organizationscited by 1
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Citing papers per year: 2025: 2.
2 papers.