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There has been a considerable amount of work on uncertainty in knowledge-based systems. This work has generally been concerned with uncertainty arising from the strength of inferences and the weight of evidence. In this paper we discuss…

Artificial Intelligence · Computer Science 2013-04-12 Steven J. Henkind

We present the fundamentals of the quantum theoretical approach we have developed in the last decade to model cognitive phenomena that resisted modeling by means of classical logical and probabilistic structures, like Boolean, Kolmogorovian…

Neurons and Cognition · Quantitative Biology 2023-02-27 Diederik Aerts , Massimiliano Sassoli de Bianchi , Sandro Sozzo , Tomas Veloz

Intercausal reasoning is a common inference pattern involving probabilistic dependence of causes of an observed common effect. The sign of this dependence is captured by a qualitative property called product synergy. The current definition…

Artificial Intelligence · Computer Science 2013-03-08 Marek J. Druzdzel , Max Henrion

Statistical convergence was introduced in connection with problems of series summation. The main idea of the statistical convergence of a sequence l is that the majority of elements from l converge and we do not care what is going on with…

General Mathematics · Mathematics 2007-05-23 Mark Burgin , Oktay Duman

Classical logic has a serious limitation in that it cannot cope with the issues of vagueness and uncertainty into which fall most modes of human reasoning. In order to provide a foundation for human knowledge representation and reasoning in…

Artificial Intelligence · Computer Science 2016-08-30 Van Hung Le

Long-term causal inference is an important but challenging problem across various scientific domains. To solve the latent confounding problem in long-term observational studies, existing methods leverage short-term experimental data.…

Machine Learning · Computer Science 2025-10-23 Weilin Chen , Ruichu Cai , Yuguang Yan , Zhifeng Hao , José Miguel Hernández-Lobato

In two recent papers, I have proposed a description of decision analysis that differs from the Bayesian picture painted by Savage, Jeffrey and other classic authors. Response to this view has been either overly enthusiastic or unduly…

Artificial Intelligence · Computer Science 2013-04-08 Ronald P. Loui

Emergence is a profound subject that straddles many scientific disciplines, including the formation of galaxies and how consciousness arises from the collective activity of neurons. Despite the broad interest that exists on this concept,…

Fuzziness and randomicity widespread exist in natural science, engineering, technology and social science. The purpose of this paper is to present a new logic - uncertain propositional logic which can deal with both fuzziness by taking…

Logic · Mathematics 2015-06-11 Maokang Luo , Wei He

Humans currently use arguments for explaining choices which are already made, or for evaluating potential choices. Each potential choice has usually pros and cons of various strengths. In spite of the usefulness of arguments in a decision…

Artificial Intelligence · Computer Science 2012-07-19 Leila Amgoud , Henri Prade

The research process includes many decisions, e.g., how to entitle and where to publish the paper. In this paper, we introduce a general framework for investigating the effects of such decisions. The main difficulty in investigating the…

Digital Libraries · Computer Science 2022-08-23 Ryoma Sato , Makoto Yamada , Hisashi Kashima

In the present article we consider the inverse fallacy, a well known cognitive heuristic experimentally tested in cognitive science, which occurs for intuitive judgments in situations of bounded rationality. We show that the quantum…

General Physics · Physics 2007-08-23 Riccardo Franco

Transparency is an essential requirement of machine learning based decision making systems that are deployed in real world. Often, transparency of a given system is achieved by providing explanations of the behavior and predictions of the…

Machine Learning · Computer Science 2021-05-18 André Artelt , Barbara Hammer

Despite significant progress has been achieved in text summarization, factual inconsistency in generated summaries still severely limits its practical applications. Among the key factors to ensure factual consistency, a reliable automatic…

Computation and Language · Computer Science 2021-09-09 Yuexiang Xie , Fei Sun , Yang Deng , Yaliang Li , Bolin Ding

Uncertainty may be taken to characterize inferences, their conclusions, their premises or all three. Under some treatments of uncertainty, the inferences itself is never characterized by uncertainty. We explore both the significance of…

Artificial Intelligence · Computer Science 2013-02-18 Henry E. Kyburg

In this paper, we present a formal analysis of temporally sensitive counterfactual conditionals. We observe a set of key metaphysical and conceptual problems in regards to counterfactual statements and time. Bearing that in mind, we present…

Logic · Mathematics 2021-10-25 Daniil Khaitovich

We make a probabilistic analysis related to some inference rules which play an important role in nonmonotonic reasoning. In a coherence-based setting, we study the extensions of a probability assessment defined on $n$ conditional events to…

Probability · Mathematics 2013-07-19 Angelo Gilio , Giuseppe Sanfilippo

With the increasing capabilities of Large Language Models (LLMs), parallel reasoning has emerged as a new inference paradigm that enhances reasoning robustness by concurrently exploring multiple lines of thought before converging on a final…

Computation and Language · Computer Science 2025-10-15 Ziqi Wang , Boye Niu , Zipeng Gao , Zhi Zheng , Tong Xu , Linghui Meng , Zhongli Li , Jing Liu , Yilong Chen , Chen Zhu , Hua Wu , Haifeng Wang , Enhong Chen

Explanations on relational data are hard to verify since the explanation structures are more complex (e.g. graphs). To verify interpretable explanations (e.g. explanations of predictions made in images, text, etc.), typically human subjects…

Artificial Intelligence · Computer Science 2024-01-08 Abisha Thapa Magar , Anup Shakya , Somdeb Sarkhel , Deepak Venugopal

The deterrent effect of military alliances is well documented and widely accepted. However, such work has typically assumed that alliances are exogenous. This is problematic as alliances may simultaneously influence the probability of…

Applications · Statistics 2019-08-21 Benjamin Campbell