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Found 8 papers, 2 papers with code
Learning Relational Rules from Rewards
To demonstrate the potential of our approach, we build a simple model of relational policy learning based on a function approximator developed in RRL.
Guidelines for the Development of Immersive Virtual Reality Software for Cognitive Neuroscience and Neuropsychology: The Development of Virtual Reality Everyday Assessment Lab (VR-EAL)
This study offers guidelines for the development of VR software in cognitive neuroscience and neuropsychology, by describing and discussing the stages of the development of Virtual Reality Everyday Assessment Lab (VR-EAL), the first neuropsychological battery in immersive VR.
Human-Computer Interaction Computers and Society Multimedia Software Engineering B.8; C.4; D.0; J.4
Validation of the Virtual Reality Neuroscience Questionnaire: Maximum Duration of Immersive Virtual Reality Sessions Without the Presence of Pertinent Adverse Symptomatology
Also, while the quality of VR software substantially modulates the maximum duration of VR sessions, age and education do not.
Human-Computer Interaction Computers and Society Multimedia B.8; C.4; D.0; J.4
Technological Competence is a Precondition for Effective Implementation of Virtual Reality Head Mounted Displays in Human Neuroscience: A Technological Review and Meta-analysis
HMDs equivalent to or greater than the commercial versions of contemporary HMDs accompanied with ergonomic interactions are suitable for implementation in cognitive neuroscience.
Human-Computer Interaction Computers and Society Multimedia B.8; C.4; D.0; J.4
A Theory of Relation Learning and Cross-domain Generalization
People readily generalize knowledge to novel domains and stimuli.
The relational processing limits of classic and contemporary neural network models of language processing
In the present study we tested the Story Gestalt model (St. John, 1992), a classic PDP model of text comprehension, and a Sequence-to-Sequence with Attention model (Bahdanau et al., 2015), a contemporary deep learning architecture for text processing.
Predicate learning in neural systems: Discovering latent generative structures
Humans learn complex latent structures from their environments (e. g., natural language, mathematics, music, social hierarchies).
Human-like generalization in a machine through predicate learning
Humans readily generalize, applying prior knowledge to novel situations and stimuli.
