Truth and Preferences -- A Game Approach for Qualitative Choice Logic

• URL: http://arxiv.org/abs/2209.12777v2
• Date: Tue, 27 Sep 2022 17:24:11 GMT
• Title: Truth and Preferences -- A Game Approach for Qualitative Choice Logic
• Authors: Robert Freiman, Michael Bernreiter
• Abstract summary: We introduce game-theoretic semantics (GTS) for qualitative Choice Logic (QCL) GTS extends classical propositional logic with an additional connective called ordered disjunction. We show that game semantics can be leveraged to derive new semantics for the language of QCL.
• Score: 2.28438857884398
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: In this paper, we introduce game-theoretic semantics (GTS) for Qualitative Choice Logic (QCL), which, in order to express preferences, extends classical propositional logic with an additional connective called ordered disjunction. Firstly, we demonstrate that game semantics can capture existing degree-based semantics for QCL in a natural way. Secondly, we show that game semantics can be leveraged to derive new semantics for the language of QCL. In particular, we present a new semantics that makes use of GTS negation and, by doing so, avoids problems with negation in existing QCL-semantics.

Related papers

• Operator-based semantics for choice programs: is choosing losing? (full version) [6.983702226751596]
  Only two-valued semantics have been studied so far. An operator-based framework allows for the definition and comparison of different semantics in a principled way.
  arXiv  Detail & Related papers  (2024-07-31T12:25:57Z)
• Learning Visual-Semantic Subspace Representations for Propositional Reasoning [49.17165360280794]
  We propose a novel approach for learning visual representations that conform to a specified semantic structure. Our approach is based on a new nuclear norm-based loss. We show that its minimum encodes the spectral geometry of the semantics in a subspace lattice.
  arXiv  Detail & Related papers  (2024-05-25T12:51:38Z)
• Open-Vocabulary Segmentation with Semantic-Assisted Calibration [73.39366775301382]
  We study open-vocabulary segmentation (OVS) through calibrating in-vocabulary and domain-biased embedding space with contextual prior of CLIP. We present a Semantic-assisted CAlibration Network (SCAN) to achieve state-of-the-art performance on open-vocabulary segmentation benchmarks.
  arXiv  Detail & Related papers  (2023-12-07T07:00:09Z)
• Description Logics Go Second-Order -- Extending EL with Universally Quantified Concepts [0.0]
  We focus on the extension of description logic $mathcalEL$. We show that for a useful fragment of the extension, the conclusions entailed by the different semantics coincide. For a slightly smaller, but still useful, fragment, we were also able to show decidability of the extension.
  arXiv  Detail & Related papers  (2023-08-16T09:37:38Z)
• Advancing Incremental Few-shot Semantic Segmentation via Semantic-guided Relation Alignment and Adaptation [98.51938442785179]
  Incremental few-shot semantic segmentation aims to incrementally extend a semantic segmentation model to novel classes. This task faces a severe semantic-aliasing issue between base and novel classes due to data imbalance. We propose the Semantic-guided Relation Alignment and Adaptation (SRAA) method that fully considers the guidance of prior semantic information.
  arXiv  Detail & Related papers  (2023-05-18T10:40:52Z)
• Not another Negation Benchmark: The NaN-NLI Test Suite for Sub-clausal Negation [59.307534363825816]
  Negation is poorly captured by current language models, although the extent of this problem is not widely understood. We introduce a natural language inference (NLI) test suite to enable probing the capabilities of NLP methods.
  arXiv  Detail & Related papers  (2022-10-06T23:39:01Z)
• Lexicographic Logic: a Many-valued Logic for Preference Representation [1.5484595752241122]
  We propose lexicographic logic, an extension of classical propositional logic that can express a variety of preferences. We argue that the new logic is an effective formalism for ranking query results according to the satisfaction level of user preferences.
  arXiv  Detail & Related papers  (2020-12-20T14:42:04Z)
• Infusing Finetuning with Semantic Dependencies [62.37697048781823]
  We show that, unlike syntax, semantics is not brought to the surface by today's pretrained models. We then use convolutional graph encoders to explicitly incorporate semantic parses into task-specific finetuning.
  arXiv  Detail & Related papers  (2020-12-10T01:27:24Z)
• Logical Semantics, Dialogical Argumentation, and Textual Entailment [0.0]
  We introduce a new dialogical system for first order classical logic which is close to natural language argumentation. We prove its completeness with respect to usual classical validity.
  arXiv  Detail & Related papers  (2020-08-17T08:04:11Z)
• Recursive Rules with Aggregation: A Simple Unified Semantics [0.6662800021628273]
  This paper describes a unified semantics for recursion with aggregation. We present a formal definition of the semantics, prove important properties of the semantics, and compare with prior semantics. We show that our semantics is simple and matches the desired results in all cases.
  arXiv  Detail & Related papers  (2020-07-26T04:42:44Z)
• Syn-QG: Syntactic and Shallow Semantic Rules for Question Generation [49.671882751569534]
  We develop SynQG, a set of transparent syntactic rules which transform declarative sentences into question-answer pairs. We utilize PropBank argument descriptions and VerbNet state predicates to incorporate shallow semantic content. In order to improve syntactic fluency and eliminate grammatically incorrect questions, we employ back-translation over the output of these syntactic rules.
  arXiv  Detail & Related papers  (2020-04-18T19:57:39Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.