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      "statement": "# Alpha-Rank evolutionary multi-agent evaluation\n\nRanks finite strategy profiles through the stationary distribution of a mutation-selection Markov chain, retaining intransitive cycles rather than forcing a scalar transitive dominance interpretation.\n\n## Scientific scope\n\nThe ranking depends on the supplied empirical strategy pool, payoffs and selection parameters. Polynomial work in the explicit payoff table can still be combinatorial in player count. The finite-intensity stationary ranking is not a Nash equilibrium or universal agent ordering. Equal-contributor marks identify Papadimitriou, Piliouras and Tuyls, not the first author.\n\n## Reading status\n\nThis is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.\n\n## People and systems\n\nShayegan Omidshafiei; Christos Papadimitriou; Georgios Piliouras; Karl Tuyls; Mark Rowland; Jean-Baptiste Lespiau; Wojciech M. Czarnecki; Marc Lanctot; Julien Perolat; Remi Munos\n\nSource-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.\n\n\n\n## Original sources\n\n- [α-Rank: Multi-Agent Evaluation by Evolution](https://arxiv.org/pdf/1903.01373v1)\n",
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