Results 221 to 230 of about 57,115 (301)

Driver Behavior Modeling with Subjective Risk‐Driven Inverse Reinforcement Learning

open access: yesAdvanced Intelligent Systems, EarlyView.
A subjective risk‐driven inverse reinforcement learning framework is proposed to model driver decision‐making. It infers drivers' risk perception and risk tolerance from driving data. A learnable risk threshold is used to regulate decisions, enabling interpretable and human‐like driving behavior decisions.
Yang Liang   +6 more
wiley   +1 more source

Causal Determinism and Preschoolers' Causal Inferences

open access: yes, 2005
Gopnik, Alison   +2 more
openaire   +1 more source

Time‐Delayed Spiking Reservoir Computing Enables Efficient Time Series Prediction

open access: yesAdvanced Intelligent Systems, EarlyView.
This study proposes time‐delayed spiking reservoir computing (TDSRC) for efficient time series prediction. By concatenating time‐lagged states, TDSRC constructs an expanded readout feature vector without altering internal reservoir dynamics. This approach enables highly accurate forecasting with significantly fewer neurons, providing a resource ...
Pin Jin   +3 more
wiley   +1 more source

ParamNet: A Physics‐Guided Deep Learning Framework for Intelligent Self‐Inversion of Vacuum Optical Levitation Systems

open access: yesAdvanced Intelligent Systems, EarlyView.
A physics‐guided deep learning framework, ParamNet, is introduced for the intelligent self‐inversion of vacuum optical tweezers. By fuzing dual‐branch time–frequency features with physical dynamical constraints, it achieves high‐accuracy calibration of trap parameters from short‐window, low‐frequency trajectories, outperforming traditional methods ...
Qi Zheng   +4 more
wiley   +1 more source

Innovative Artificial Intelligence‐Assisted Systems for Social Science Research: Architecture Design and Applied Practice

open access: yesAI &Innovation, EarlyView.
ABSTRACT The rapid advancement of large language model (LLM) technology is profoundly transforming the practice of social science research. Scholarly discussions on Artificial Intelligence (AI)'s role in social science research can be organised into three levels: AI as a research tool, AI as a methodological infrastructure and AI as a quasi‐cognitive ...
Jie Xiong
wiley   +1 more source

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