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Evidential cooperation in large worlds

Evidential Cooperation in Large worlds (ECL) refers to the idea that, since the universe may be very large, it likely contains many agents very similar to oneself, and that by taking actions that are good for these agents, we learn that they take actions that are good for us. The idea of ECL was introduced in Oesterheld, 2017 as MSR (Multiverse-wide superationality).

Further Reading

Oesterheld, Caspar (2017) Multiverse-wide Cooperation via Correlated Decision Making, Center on Long-Term Risk, August 10.

Oesterheld, Caspar (2017) Multiverse-wide cooperation, talk at EA Global: London 2017, Effective Altruism Global, October 27.

Treutlein, Johannes (2023) Modeling evidential cooperation in large worlds, arXiv preprint, arXiv:2307.04879.

Finnveden, Lukas (2023) ECL with AI, Lukas Finnveden's Substack, August 20.

Oesterheld, Caspar (2017) Overview: Evidential Cooperation in Large Worlds (ECL), Center on Long-Term Risk, November 2.