Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for Multi-Agent Intelligence Research

March 02, 2019 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Joel Z. Leibo, Edward Hughes, Marc Lanctot, Thore Graepel arXiv ID 1903.00742 Category cs.AI: Artificial Intelligence Cross-listed cs.GT, cs.MA, cs.NE, q-bio.NC Citations 119 Venue arXiv.org Last Checked 3 months ago
Abstract
Evolution has produced a multi-scale mosaic of interacting adaptive units. Innovations arise when perturbations push parts of the system away from stable equilibria into new regimes where previously well-adapted solutions no longer work. Here we explore the hypothesis that multi-agent systems sometimes display intrinsic dynamics arising from competition and cooperation that provide a naturally emergent curriculum, which we term an autocurriculum. The solution of one social task often begets new social tasks, continually generating novel challenges, and thereby promoting innovation. Under certain conditions these challenges may become increasingly complex over time, demanding that agents accumulate ever more innovations.
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