Common abductive explanations in first order logic

We build upon a recent definition of a common explanation for the label shared by a group of observations. The motivation stems from explaining how a specific action, when playing a card game, leads to an acceptable reward at the end of the game. Since there are various ways to achieve this goal, gr...

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Vydáno v:	Machine learning Ročník 114; číslo 12; s. 264
Hlavní autoři:	Rouveirol, Céline, Soldano, Henry, Kazi Aoual, Malik, Ventos, Véronique
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.12.2025 Springer Nature B.V
Témata:	Algorithms Artificial Intelligence Card games Computer Science Control Decision trees Logic Machine Learning Mechatronics Natural Language Processing (NLP) Robotics Simulation and Modeling Inductive logic programming Abductive explanation
ISSN:	0885-6125, 1573-0565
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Abstract	We build upon a recent definition of a common explanation for the label shared by a group of observations. The motivation stems from explaining how a specific action, when playing a card game, leads to an acceptable reward at the end of the game. Since there are various ways to achieve this goal, groups of acceptable trajectories are first extracted from a rule-based ILP model. Subsequently, common explanations are enumerated for each group of trajectories. A significant contribution of this article is the introduction of a new definition of preferred common explanations: they must be both subset-minimal and maximally instantiated. These so-called leq-minimal common explanations ( leq-MCE s for short) happen to be subsets of the least general generalisation of the observations in the group. We propose efficient algorithms to enumerate leq-MCE s and a scheme to extract a diverse subset of these leq-MCEs to be presented to human interlocutors. Experiments are conducted on a card game.
AbstractList	We build upon a recent definition of a common explanation for the label shared by a group of observations. The motivation stems from explaining how a specific action, when playing a card game, leads to an acceptable reward at the end of the game. Since there are various ways to achieve this goal, groups of acceptable trajectories are first extracted from a rule-based ILP model. Subsequently, common explanations are enumerated for each group of trajectories. A significant contribution of this article is the introduction of a new definition of preferred common explanations: they must be both subset-minimal and maximally instantiated. These so-called leq-minimal common explanations (leq-MCEs for short) happen to be subsets of the least general generalisation of the observations in the group. We propose efficient algorithms to enumerate leq-MCEs and a scheme to extract a diverse subset of these leq-MCEs to be presented to human interlocutors. Experiments are conducted on a card game. We build upon a recent definition of a common explanation for the label shared by a group of observations. The motivation stems from explaining how a specific action, when playing a card game, leads to an acceptable reward at the end of the game. Since there are various ways to achieve this goal, groups of acceptable trajectories are first extracted from a rule-based ILP model. Subsequently, common explanations are enumerated for each group of trajectories. A significant contribution of this article is the introduction of a new definition of preferred common explanations: they must be both subset-minimal and maximally instantiated. These so-called leq-minimal common explanations ( leq-MCE s for short) happen to be subsets of the least general generalisation of the observations in the group. We propose efficient algorithms to enumerate leq-MCE s and a scheme to extract a diverse subset of these leq-MCEs to be presented to human interlocutors. Experiments are conducted on a card game.
ArticleNumber	264
Author	Kazi Aoual, Malik Ventos, Véronique Rouveirol, Céline Soldano, Henry
Author_xml	– sequence: 1 givenname: Céline surname: Rouveirol fullname: Rouveirol, Céline organization: LIPN, UMR-CNRS 7030, Université Sorbonne Paris-Nord – sequence: 2 givenname: Henry surname: Soldano fullname: Soldano, Henry email: soldano@lipn.univ-paris13.fr organization: NukkAI, LIPN, UMR-CNRS 7030, Université Sorbonne Paris-Nord – sequence: 3 givenname: Malik surname: Kazi Aoual fullname: Kazi Aoual, Malik organization: NukkAI, LIPN, UMR-CNRS 7030, Université Sorbonne Paris-Nord – sequence: 4 givenname: Véronique surname: Ventos fullname: Ventos, Véronique organization: NukkAI
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Snippet	We build upon a recent definition of a common explanation for the label shared by a group of observations. The motivation stems from explaining how a specific...
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SubjectTerms	Algorithms Artificial Intelligence Card games Computer Science Control Decision trees Logic Machine Learning Mechatronics Natural Language Processing (NLP) Robotics Simulation and Modeling
Title	Common abductive explanations in first order logic
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