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“Shapley value” as a book category gathers works centered on the theory and practice of fairly attributing value, cost, payoff, or credit among collaborators based on marginal contributions. Anchored in cooperative game theory, it spans foundational texts on the Shapley value and related solution concepts, computational and approximation methods, and applications across economics, operations research, political science (voting power), law and policy (cost sharing), and business analytics. The category also includes modern applications in data science and AI—especially explainable machine learning and feature attribution (e.g., SHAP)—along with case studies in revenue and risk allocation, marketing attribution, and team evaluation. Titles range from rigorous mathematical treatments and research monographs to accessible primers, practitioner guides, and historical or biographical works on Lloyd Shapley and the evolution of cooperative game theory. The unifying theme is principled, contribution-based fairness in multi-agent settings.

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