Results 111 to 120 of about 74,791 (289)

Possible World Semantics and True‐True Counterfactuals [PDF]

open access: yesPacific Philosophical Quarterly, 2015
AbstractThe standard semantics for counterfactuals ensures that any counterfactual with a true antecedent and true consequent is itself true. There have been many recent attempts to amend the standard semantics to avoid this result. I show that these proposals invalidate a number of further principles of the standard logic of counterfactuals.
openaire   +3 more sources

Decoding Naturalistic Episodic Memory with Artificial Intelligence and Brain‐Machine Interface

open access: yesAdvanced Science, EarlyView.
Episodic memory weaves together what, where, and when of experience into a personal narrative. Cutting‐edge AI models may decode this intricate process in real‐life settings, revealing how neural activity encodes naturalistic memories. By merging AI with brain–machine interfaces, researchers are edging closer to mapping and even engineering memory ...
Dong Song
wiley   +1 more source

Towards a New Theory of Modal Fictionalism

open access: yesOstium, 2017
In our everyday discourse, most of us use modal statements to express possibility, necessity, or contingency. Logicians, linguists, and philosophers of language tend to use the possible world discourse to analyse the semantics of this kind of sentences ...
Áron Dombrovszski
doaj  

Multi-Agent Only-Knowing Revisited [PDF]

open access: yes, 2010
Levesque introduced the notion of only-knowing to precisely capture the beliefs of a knowledge base. He also showed how only-knowing can be used to formalize non-monotonic behavior within a monotonic logic. Despite its appeal, all attempts to extend only-
Belle, Vaishak, Lakemeyer, Gerhard
core   +2 more sources

Learnable Diffusion Framework for Mouse V1 Neural Decoding

open access: yesAdvanced Science, EarlyView.
We introduce Sensorium‐Viz, a diffusion‐based framework for reconstructing high‐fidelity visual stimuli from mouse primary visual cortex activity. By integrating a novel spatial embedding module with a Diffusion Transformer (DiT) and a synthetic‐response augmentation strategy, our model outperforms state‐of‐the‐art fMRI‐based baselines, enabling robust
Kaiwen Deng   +2 more
wiley   +1 more source

Quasi-SLCA based Keyword Query Processing over Probabilistic XML Data

open access: yes, 2013
The probabilistic threshold query is one of the most common queries in uncertain databases, where a result satisfying the query must be also with probability meeting the threshold requirement. In this paper, we investigate probabilistic threshold keyword
Li, Jianxin   +3 more
core   +2 more sources

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

open access: yesAdvanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju   +5 more
wiley   +1 more source

Decidability of Multi-agent Logic of Computation Trees $\mathcal{CTLK}^{Rel}$

open access: yesИзвестия Иркутского государственного университета: Серия "Математика"
We continue to explore the multi-agent logic of computational trees relative to the relational Kripke semantics of possible worlds: we investigate the question of logical solvability, the complexity of model construction, feasibility testing, and ...
S.I. Bashmakov, K. A. Smelykh
doaj   +1 more source

Multi-Agent Only Knowing

open access: yes, 2000
Levesque introduced a notion of ``only knowing'', with the goal of capturing certain types of nonmonotonic reasoning. Levesque's logic dealt with only the case of a single agent.
Halpern, Joseph Y., Lakemeyer, Gerhard
core   +2 more sources

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

open access: yesAdvanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu   +4 more
wiley   +1 more source

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