A systematic review and meta-analysis of machine learning, deep learning, and ensemble learning approaches in predicting EV charging behavior

E Yaghoubi, E Yaghoubi, A Khamees, D Razmi… - … Applications of Artificial …, 2024 - Elsevier
Abstract Machine learning (ML) and deep learning (DL) have enabled algorithms to
autonomously acquire knowledge from data, facilitating predictive and decision-making …

Hippocampal contributions to social and cognitive deficits in autism spectrum disorder

SM Banker, X Gu, D Schiller, JH Foss-Feig - Trends in neurosciences, 2021 - cell.com
Autism spectrum disorder (ASD) is characterized by hallmark impairments in social
functioning. Nevertheless, nonsocial cognition, including hippocampus-dependent spatial …

An introduction to deep reinforcement learning

V François-Lavet, P Henderson, R Islam… - … and Trends® in …, 2018 - nowpublishers.com
Deep reinforcement learning is the combination of reinforcement learning (RL) and deep
learning. This field of research has been able to solve a wide range of complex …

[LIVRE][B] Explain me this: Creativity, competition, and the partial productivity of constructions

AE Goldberg - 2019 - books.google.com
Why our use of language is highly creative yet also constrained We use words and phrases
creatively to express ourselves in ever-changing contexts, readily extending language …

Experience replay is associated with efficient nonlocal learning

Y Liu, MG Mattar, TEJ Behrens, ND Daw, RJ Dolan - Science, 2021 - science.org
INTRODUCTION Adaptive decision-making requires assimilation of reward information to
guide subsequent choices. However, actions and outcomes are often separated by time and …

The hippocampus as a predictive map

KL Stachenfeld, MM Botvinick, SJ Gershman - Nature neuroscience, 2017 - nature.com
A cognitive map has long been the dominant metaphor for hippocampal function, embracing
the idea that place cells encode a geometric representation of space. However, evidence for …

Planning in the brain

MG Mattar, M Lengyel - Neuron, 2022 - cell.com
Recent breakthroughs in artificial intelligence (AI) have enabled machines to plan in tasks
previously thought to be uniquely human. Meanwhile, the planning algorithms implemented …

The successor representation in human reinforcement learning

I Momennejad, EM Russek, JH Cheong… - Nature human …, 2017 - nature.com
Theories of reward learning in neuroscience have focused on two families of algorithms
thought to capture deliberative versus habitual choice.'Model-based'algorithms compute the …

Prioritized memory access explains planning and hippocampal replay

MG Mattar, ND Daw - Nature neuroscience, 2018 - nature.com
To make decisions, animals must evaluate candidate choices by accessing memories of
relevant experiences. Yet little is known about which experiences are considered or ignored …

A map of abstract relational knowledge in the human hippocampal–entorhinal cortex

MM Garvert, RJ Dolan, TEJ Behrens - elife, 2017 - elifesciences.org
The hippocampal–entorhinal system encodes a map of space that guides spatial navigation.
Goal-directed behaviour outside of spatial navigation similarly requires a representation of …