A Game-Theoretic Perspective on Inconsistency Handling
Authors: Yakoub Salhi
IJCAI 2025 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | This paper introduces a game-theoretic framework for restoring consistency in propositional bases. The process is modeled as an interactive dialogue between two agents: a Proponent, who seeks to isolate a unique, consistent subset by posing strategic questions, and an Opponent, who aims to obstruct that goal through adversarial responses. We show that this framework provides a foundation for quantifying the effort involved in restoring consistency, revealing a connection between this effort and entropy in information theory. Finally, we demonstrate how the quantified restoration effort can serve as a basis for measuring inconsistency. |
| Researcher Affiliation | Academia | Yakoub Salhi Univ. Artois, CNRS, CRIL, F-62300 Lens, France EMAIL |
| Pseudocode | Yes | Algorithm 1 Greedy Algorithm for Approximating Iw mc Require: A PB K and the set of its MCSes S = MCS(K) 1: function BUILDTREE(S) 2: if |S| = 1 then 3: return a leaf node identifying the single MCS in S 4: end if 5: Let φ = arg minφ S S\T S G(φ, S) 6: Recursively build left and right subtrees: Tl BUILDTREE(S φ) Tr BUILDTREE(Sφ) 7: return the tree (φ, Tl, Tr) 8: end function 9: BUILDTREE(S) |
| Open Source Code | No | The paper does not provide any statement about releasing source code, nor does it include links to a code repository. |
| Open Datasets | No | The paper introduces a game-theoretic framework and an inconsistency measure, but it does not conduct empirical experiments using specific datasets. Therefore, there is no mention of open datasets. |
| Dataset Splits | No | The paper focuses on theoretical development and does not describe any experiments that would involve dataset splits. |
| Hardware Specification | No | The paper is theoretical and does not describe any experimental setup or specific hardware used for computations. |
| Software Dependencies | No | The paper describes a theoretical framework and an algorithm but does not specify any software dependencies or their versions. |
| Experiment Setup | No | The paper is theoretical and does not include an experimental section with specific setup details like hyperparameters or training configurations. |