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To operate intelligently in the world, an agent must reason about its actions. The consequences of an action are a function of both the state of the world and the action itself. Many aspects of the world are inherently stochastic, so a…

Artificial Intelligence · Computer Science 2013-04-05 Peter Haddawy

It is proposed that the ability of humans to flourish in diverse environments and evolve complex cultures reflects the following two underlying cognitive transitions. The transition from the coarse-grained associative memory of Homo habilis…

Neurons and Cognition · Quantitative Biology 2013-08-26 Liane Gabora , Diederik Aerts

An exhaustive survey of categorical propositions is proposed in the present paper, both with respect to their nature and the logical problems raised by them. Through a comparative analysis of Term Logic and First-Order Logic, it is shown…

Logic in Computer Science · Computer Science 2022-04-15 Fabien Schang , George Englebretsen , J. -Martín Castro-Manzano

In this talk - based on the results of a forthcoming paper (Coletti, Scozzafava and Vantaggi 2002), presented also by one of us at the Conference on "Non Classical Logic, Approximate Reasoning and Soft-Computing" (Anacapri, Italy, 2001) -…

Probability · Mathematics 2007-05-23 Giulianella Coletti , Romano Scozzafava , Barbara Vantaggi

We present an epistemic action theory for tractable epistemic reasoning as an extension to the h-approximation (HPX) theory. In contrast to existing tractable approaches, the theory supports functional fluents and postdictive reasoning with…

Artificial Intelligence · Computer Science 2020-11-26 Manfred Eppe

Humans display a tendency to pay more attention to bad outcomes, often in a disproportionate way relative to their statistical occurrence. They also display euphorism, as well as a preference for the current state of affairs (status quo…

Artificial Intelligence · Computer Science 2022-03-24 Michel de Lara

This work investigates the algorithmic complexity of non-classical logics, focusing on superintuitionistic and modal systems. It is shown that propositional logics are usually polynomial-time reducible to their fragments with at most two…

Logic in Computer Science · Computer Science 2025-12-30 Mikhail Rybakov

This paper presents a new system of logic, LF, that is intended to be used as the foundation of the formalization of science. That is, deductive validity according to LF is to be used as the criterion for assessing what follows from the…

Logic · Mathematics 2024-01-23 Zachary Goodsell , Juhani Yli-Vakkuri

This paper develops an algorithmic-based approach for proving inductive properties of propositional sequent systems such as admissibility, invertibility, cut-elimination, and identity expansion. Although undecidable in general, these…

Logic in Computer Science · Computer Science 2021-01-11 Carlos Olarte , Elaine Pimentel , Camilo Rocha

We present probabilistic approaches to check the validity of selected connexive principles within the setting of coherence. Connexive logics emerged from the intuition that conditionals of the form "If $\sim A$, then $A$", should not hold,…

Logic · Mathematics 2021-09-13 Niki Pfeifer , Giuseppe Sanfilippo

Large language models (LLMs) are increasingly used in domains where causal reasoning matters, yet it remains unclear whether their judgments reflect normative causal computation, human-like shortcuts, or brittle pattern matching. We…

Artificial Intelligence · Computer Science 2026-03-16 Hanna M. Dettki , Charley M. Wu , Bob Rehder

In this paper, we propose how to use objective arguments grounded in statistical mechanics concepts in order to obtain a single number, obtained after aggregation, which would allow to rank "agents", "opinions", ..., all defined in a very…

Physics and Society · Physics 2024-05-02 Marcel Ausloos , Giulia Rotundo , Roy Cerqueti

In everyday life it happens that a person has to reason about what other people think and how they behave, in order to achieve his goals. In other words, an individual may be required to adapt his behaviour by reasoning about the others'…

Artificial Intelligence · Computer Science 2008-12-18 Francesco Buccafurri , Gianluca Caminiti

Bayesian inference has theoretical attractions as a principled framework for reasoning about beliefs. However, the motivations of Bayesian inference which claim it to be the only 'rational' kind of reasoning do not apply in practice. They…

Machine Learning · Statistics 2022-11-14 Sebastian Farquhar

It is here proposed an analysis of symbolic and sub-symbolic models for studying cognitive processes, centered on emergence and logical openness notions.The Theory of Logical Openness connects the Physics of system/environment relationships…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Ignazio Licata

Pre-trained language models (PLMs) have shown impressive performance in various language tasks. However, they are prone to spurious correlations, and often generate illusory information. In real-world applications, PLMs should justify…

Computation and Language · Computer Science 2023-10-31 Zheyuan Zhang , Shane Storks , Fengyuan Hu , Sungryull Sohn , Moontae Lee , Honglak Lee , Joyce Chai

Epistemic reasoning requires agents to infer the state of the world from partial observations and information about other agents' knowledge. Prior work evaluating LLMs on canonical epistemic puzzles interpreted their behavior through a…

Computation and Language · Computer Science 2026-03-24 Adi Gabay , Gabriel Stanovsky , Liat Peterfreund

Sequential propositional logic deviates from ordinary propositional logic by taking into account that during the sequential evaluation of a propositional statement,atomic propositions may yield different Boolean values at repeated…

Logic in Computer Science · Computer Science 2011-06-28 J. A. Bergstra , A. Ponse

In this work, we develop a novel reasoning approach to enhance the performance of large language models (LLMs) in future occupation prediction. In this approach, a reason generator first derives a ``reason'' for a user using his/her past…

Computation and Language · Computer Science 2026-04-24 Shan Dong , Palakorn Achananuparp , Hieu Hien Mai , Lei Wang , Yao Lu , Ee-Peng Lim

In this paper, we set forth a new vision of reinforcement learning developed by us over the past few years, one that yields mathematically rigorous solutions to longstanding important questions that have remained unresolved: (i) how to…

Machine Learning · Computer Science 2014-05-28 Sridhar Mahadevan , Bo Liu , Philip Thomas , Will Dabney , Steve Giguere , Nicholas Jacek , Ian Gemp , Ji Liu
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