Shapley Revisited: Tractable Responsibility Measures for Query Answers
This work addresses a computational bottleneck in database responsibility attribution, offering a tractable alternative for database practitioners, though it is incremental as it builds on existing Shapley value concepts.
The paper tackles the computational intractability of Shapley-based responsibility measures for database query answers by introducing weighted sums of minimal supports (WSMS), which satisfy intuitive properties and are proven equivalent to Shapley values under a defined cooperative game, achieving tractable data complexity for unions of conjunctive queries.
The Shapley value, originating from cooperative game theory, has been employed to define responsibility measures that quantify the contributions of database facts to obtaining a given query answer. For non-numeric queries, this is done by considering a cooperative game whose players are the facts and whose wealth function assigns 1 or 0 to each subset of the database, depending on whether the query answer holds in the given subset. While conceptually simple, this approach suffers from a notable drawback: the problem of computing such Shapley values is #P-hard in data complexity, even for simple conjunctive queries. This motivates us to revisit the question of what constitutes a reasonable responsibility measure and to introduce a new family of responsibility measures -- weighted sums of minimal supports (WSMS) -- which satisfy intuitive properties. Interestingly, while the definition of WSMSs is simple and bears no obvious resemblance to the Shapley value formula, we prove that every WSMS measure can be equivalently seen as the Shapley value of a suitably defined cooperative game. Moreover, WSMS measures enjoy tractable data complexity for a large class of queries, including all unions of conjunctive queries. We further explore the combined complexity of WSMS computation and establish (in)tractability results for various subclasses of conjunctive queries.