Abstract

Over the last few years, the Shapley value, a solution concept from cooperative game theory, has found numerous applications in machine learning. In this paper, we first discuss fundamental concepts of cooperative game theory and axiomatic properties of the Shapley value. Then we give an overview of the most important applications of the Shapley value in machine learning: feature selection, explainability, multi-agent reinforcement learning, ensemble pruning, and data valuation. We examine the most crucial limitations of the Shapley value and point out directions for future research.

Citation impact

257
total citations
FWCI
23.99
Percentile
100%
References
76
Citations per year

Authors

7

Topics & keywords

Keywords
  • Shapley value
  • Axiom
  • Cooperative game theory
  • Computer science
  • Valuation (finance)
  • Artificial intelligence
  • Game theory
  • Reinforcement learning
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Funding