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Understanding how humans revise their beliefs in light of new information is crucial for developing AI systems which can effectively model, and thus align with, human reasoning. While theoretical belief revision frameworks rely on a set of…

Artificial Intelligence · Computer Science 2025-06-12 Stylianos Loukas Vasileiou , Antonio Rago , Maria Vanina Martinez , William Yeoh

Given the emergent reasoning abilities of large language models, information retrieval is becoming more complex. Rather than just retrieve a document, modern information retrieval systems advertise that they can synthesize an answer based…

Information Retrieval · Computer Science 2024-02-29 Gregory Coppola

Probability theory, epistemically interpreted, provides an excellent, if not the best available account of inductive reasoning. This is so because there are general and definite rules for the change of subjective probabilities through…

Artificial Intelligence · Computer Science 2013-04-10 Wolfgang Spohn

Asking good questions in large-scale, open-domain conversational systems is quite significant yet rather untouched. This task, substantially different from traditional question generation, requires to question not only with various patterns…

Computation and Language · Computer Science 2018-05-15 Yansen Wang , Chenyi Liu , Minlie Huang , Liqiang Nie

Human beings possess the most sophisticated computational machinery in the known universe. We can understand language of rich descriptive power, and communicate in the same environment with astonishing clarity. Two of the many contributors…

Computation and Language · Computer Science 2021-01-01 Karthikeya Ramesh Kaushik , Andrea E. Martin

Nonmonotonic reasoning is a pattern of reasoning that allows an agent to make and retract (tentative) conclusions from inconclusive evidence. This paper gives a possible-worlds interpretation of the nonmonotonic reasoning problem based on…

Artificial Intelligence · Computer Science 2013-04-10 Carl Kadie

The purpose of the paper is to introduce a new approach of planning called Assumption-Based Planning. This approach is a very interesting way to devise a planner based on a multi-agent system in which the production of a global shared plan…

Artificial Intelligence · Computer Science 2018-10-22 Damien Pellier , Humbert Fiorino

Training a model with access to human explanations can improve data efficiency and model performance on in- and out-of-domain data. Adding to these empirical findings, similarity with the process of human learning makes learning from…

Computation and Language · Computer Science 2022-04-20 Mareike Hartmann , Daniel Sonntag

Even today, the concept of entropy is perceived by many as quite obscure. The main difficulty is analyzed as being fundamentally due to the subjectivity and anthropocentrism of the concept that prevent us to have a sufficient distance to…

General Physics · Physics 2022-10-21 Didier Lairez

Inspired by e-participation systems, in this paper we propose a new model to represent human debates and methods to obtain collective conclusions from them. This model overcomes drawbacks of existing approaches by allowing users to…

Artificial Intelligence · Computer Science 2020-07-15 Jordi Ganzer , Natalia Criado , Maite Lopez-Sanchez , Simon Parsons , Juan A. Rodriguez-Aguilar

This paper describes a new entropy-style of equation that may be useful in a general sense, but can be applied to a cognitive model with related processes. The model is based on the human brain, with automatic and distributed pattern…

Artificial Intelligence · Computer Science 2021-04-23 Kieran Greer

One of the greatest research challenges of this century is to understand the neural basis for how behavior emerges in brain-body-environment systems. To this end, research has flourished along several directions but have predominantly…

Neurons and Cognition · Quantitative Biology 2021-06-10 Madhavun Candadai

A hallmark of human intelligence is the ability to adapt to new situations, by applying learned rules to new content (systematicity) and thereby enabling an open-ended number of inferences and actions (generativity). Here, we propose that…

Neurons and Cognition · Quantitative Biology 2021-08-10 Randall C. O'Reilly , Charan Ranganath , Jacob L. Russin

There is a long history in game theory on the topic of Bayesian or "rational" learning, in which each player maintains beliefs over a set of alternative behaviours, or types, for the other players. This idea has gained increasing interest…

Artificial Intelligence · Computer Science 2016-03-03 Stefano V. Albrecht , Jacob W. Crandall , Subramanian Ramamoorthy

Interpretability is an elusive but highly sought-after characteristic of modern machine learning methods. Recent work has focused on interpretability via $\textit{explanations}$, which justify individual model predictions. In this work, we…

Machine Learning · Computer Science 2019-10-31 David Alvarez-Melis , Hal Daumé , Jennifer Wortman Vaughan , Hanna Wallach

The article further develops and formalizes a theory of friendly dialogue in an AI System of Dr. Watson type, as proposed in our previous publication[4],[19]. The main principle of this type of AI is to guide the user toward a solution in a…

Artificial Intelligence · Computer Science 2024-07-31 Saveli Goldberg , Vladimir Sluchak

Current approaches in paraphrase generation and detection heavily rely on a single general similarity score, ignoring the intricate linguistic properties of language. This paper introduces two new tasks to address this shortcoming by…

Computation and Language · Computer Science 2024-07-17 Jan Philip Wahle , Bela Gipp , Terry Ruas

A fascinating hypothesis is that human and animal intelligence could be explained by a few principles (rather than an encyclopedic list of heuristics). If that hypothesis was correct, we could more easily both understand our own…

Machine Learning · Computer Science 2022-08-02 Anirudh Goyal , Yoshua Bengio

Analogy is a central faculty of human intelligence, enabling abstract patterns discovered in one domain to be applied to another. Despite its central role in cognition, the mechanisms by which Transformers acquire and implement analogical…

Artificial Intelligence · Computer Science 2026-05-28 Gouki Minegishi , Jingyuan Feng , Hiroki Furuta , Takeshi Kojima , Yusuke Iwasawa , Yutaka Matsuo

Creativity relates to the ability to generate novel and effective ideas in the areas of interest. How are such creative ideas generated? One possible mechanism that supports creative ideation and is gaining increased empirical attention is…

Computation and Language · Computer Science 2025-08-08 Anna Wróblewska , Marceli Korbin , Yoed N. Kenett , Daniel Dan , Maria Ganzha , Marcin Paprzycki
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