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Prior work on generating explanations in a planning and decision-making context has focused on providing the rationale behind an AI agent's decision making. While these methods provide the right explanations from the explainer's…

Artificial Intelligence · Computer Science 2020-10-20 Mehrdad Zakershahrak , Shashank Rao Marpally , Akshay Sharma , Ze Gong , Yu Zhang

Using Answer Set Programming in an Inference-Based approach to Natural Language Semantics

Computation and Language · Computer Science 2007-05-23 Farid Nouioua , Pascal Nicolas

There are some recent approaches and results about the use of answer-set programming for specifying counterfactual interventions on entities under classification, and reasoning about them. These approaches are flexible and modular in that…

Artificial Intelligence · Computer Science 2021-08-26 Leopoldo Bertossi

Matching plays a vital role in the rational allocation of resources in many areas, ranging from market operation to people's daily lives. In economics, the term matching theory is coined for pairing two agents in a specific market to reach…

Social and Information Networks · Computer Science 2021-03-17 Jing Ren , Feng Xia , Xiangtai Chen , Jiaying Liu , Mingliang Hou , Ahsan Shehzad , Nargiz Sultanova , Xiangjie Kong

We present a novel framework for integrating prior knowledge into discriminative classifiers. Our framework allows discriminative classifiers such as Support Vector Machines (SVMs) to utilize prior knowledge specified in the generative…

Artificial Intelligence · Computer Science 2011-09-29 G. DeJong , A. Epshteyn

Starting from the observation that rational closure has the undesirable property of being an "all or nothing" mechanism, we here propose a multipreferential semantics, which enriches the preferential semantics underlying rational closure in…

Artificial Intelligence · Computer Science 2018-01-23 Laura Giordano , Valentina Gliozzi

We propose a quantitative and qualitative analysis of the performances of statistical models for frame semantic structure extraction. We report on a replication study on FrameNet 1.7 data and show that preprocessing toolkits play a major…

Computation and Language · Computer Science 2019-01-23 Alexandre Kabbach

The problem of relevance ranking consists of sorting a set of objects with respect to a given criterion. Since users may prefer different relevance criteria, the ranking algorithms should be adaptable to the user needs. Two main approaches…

Machine Learning · Computer Science 2023-11-06 Leonardo Rigutini , Tiziano Papini , Marco Maggini , Franco Scarselli

A mathematical model of Subject behaviour choice is proposed. The background of the model is the concept of two preference relations determining Subject behaviour. These are an "internal" or subjective preference relation and an "external"…

Logic · Mathematics 2025-10-20 Valeriy K. Bulitko

We propose a novel logic, called Frame Logic (FL), that extends first-order logic (with recursive definitions) using a construct Sp(.) that captures the implicit supports of formulas -- the precise subset of the universe upon which their…

Logic in Computer Science · Computer Science 2022-09-27 Adithya Murali , Lucas Peña , Christof Löding , P. Madhusudan

Logic Programs with Ordered Disjunction (LPODs) extend classical logic programs with the capability of expressing alternatives with decreasing degrees of preference in the heads of program rules. Despite the fact that the operational…

Artificial Intelligence · Computer Science 2022-05-09 Angelos Charalambidis , Panos Rondogiannis , Antonis Troumpoukis

Preference tuning is a crucial process for aligning deep generative models with human preferences. This survey offers a thorough overview of recent advancements in preference tuning and the integration of human feedback. The paper is…

Computation and Language · Computer Science 2024-11-05 Genta Indra Winata , Hanyang Zhao , Anirban Das , Wenpin Tang , David D. Yao , Shi-Xiong Zhang , Sambit Sahu

This paper builds on the recent ASPIC+ formalism, to develop a general framework for argumentation with preferences. We motivate a revised definition of conflict free sets of arguments, adapt ASPIC+ to accommodate a broader range of…

Artificial Intelligence · Computer Science 2018-04-19 Sanjay Modgil , Henry Prakken

User preference learning is generally a hard problem. Individual preferences are typically unknown even to users themselves, while the space of choices is infinite. Here we study user preference learning from information-theoretic…

Machine Learning · Computer Science 2023-11-27 Tanya Ignatenko , Kirill Kondrashov , Marco Cox , Bert de Vries

Many logic programming based approaches can be used to describe and solve combinatorial search problems. On the one hand there are definite programs and constraint logic programs that compute a solution as an answer substitution to a query…

Logic in Computer Science · Computer Science 2007-05-23 Nikolay Pelov , Emmanuel De Mot , Maurice Bruynooghe

We study how linear orders can be employed to realise choice functions for which the set of potential choices is restricted, i.e., the possible choice is not possible among the full powerset of all alternatives. In such restricted settings,…

Artificial Intelligence · Computer Science 2025-09-05 Kai Sauerwald , Kenneth Skiba , Eduardo Fermé , Thomas Meyer

This paper studies the stable model semantics of logic programs with (abstract) constraint atoms and their properties. We introduce a succinct abstract representation of these constraint atoms in which a constraint atom is represented…

Artificial Intelligence · Computer Science 2009-05-01 Yi-Dong Shen , Jia-Huai You , Li-Yan Yuan

Recently, ranking-based semantics is proposed to rank-order arguments from the most acceptable to the weakest one(s), which provides a graded assessment to arguments. In general, the ranking on arguments is derived from the strength values…

Artificial Intelligence · Computer Science 2014-12-04 Fuan Pu , Jian Luo , Yulai Zhang , Guiming Luo

This paper addresses the problem of preference learning, which aims to align robot behaviors through learning user specific preferences (e.g. "good pull-over location") from visual demonstrations. Despite its similarity to learning factual…

Robotics · Computer Science 2025-01-16 Sadanand Modak , Noah Patton , Isil Dillig , Joydeep Biswas

In classical logic, nonBoolean fluents, such as the location of an object, can be naturally described by functions. However, this is not the case in answer set programs, where the values of functions are pre-defined, and nonmonotonicity of…

Artificial Intelligence · Computer Science 2023-07-21 Michael Bartholomew , Joohyung Lee
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