Article
Psychology, Experimental
Chisom O. Obasih, Sahil Luthra, Frederic Dick, Lori L. Holt
Summary: Multiple lines of research in education have developed various training approaches that facilitate category learning. However, these studies often simplify the complexity of real-world input. In this study, we challenged the assumption that these simplified studies reflect the actual process of category learning by creating a complex auditory category learning paradigm. The results demonstrate that learning in complex input conditions is not as influenced by training regime manipulation as previously thought.
Article
Biology
Yafit Gabay, Avi Karni, Lori L. Holt
Summary: Research suggests that humans can generate complex categories based on imperfect sensory input. This study examines the possibility of incidental experiences generating lasting category knowledge. Results showed that sound category learning can occur incidentally during a visuomotor task, even when the sound categories are not necessary for task success. Furthermore, this incidental learning can lead to the consolidation of new knowledge and support generalization of learning.
Article
Psychology, Mathematical
Leeland L. Rogers, Su Hyoun Park, Timothy J. Vickery
Summary: The study found that visual statistical learning is influenced by the learning goals of the observer and their prior knowledge about the structure of the world. Different categories of stimuli have an impact on learning effects, while natural categories also have an influence on learning outcomes.
PSYCHONOMIC BULLETIN & REVIEW
(2021)
Article
Psychology, Multidisciplinary
Yafit Gabay, Casey L. Roark, Lori L. Holt
Summary: Categorization has a deep impact on behavior. This study investigates whether category learning is supported by a single system or multiple systems, using nonspeech auditory category learning challenges. The results show that individuals with dyslexia have impaired information-integration category learning but preserved rule-based category learning. Furthermore, dyslexia participants show reduced use of optimal procedural-based strategies. These findings suggest the existence of multiple category learning systems and provide insights into the difficulty in phonetic category acquisition in dyslexia.
PSYCHOLOGICAL SCIENCE
(2023)
Article
Psychology, Mathematical
Emily M. Heffernan, Juliana D. Adema, Michael L. Mack
Summary: Successful categorization requires careful coordination of attention, representation, and decision making. Neural activation from different brain regions is associated with category decisions, with lateral prefrontal cortex activation specifically linked to exemplar-based model predictions of trial-by-trial category evidence. These brain regions support distinct functions that contribute to successful category learning.
PSYCHONOMIC BULLETIN & REVIEW
(2021)
Article
Computer Science, Information Systems
Kainat Mustafa, Sajjad Khan, Sheraz Aslam, Herodotos Herodotou, Nouman Ashraf, Amil Daraz, Tamim Alkhalifah
Summary: This review article comprehensively explores the application of machine learning and deep learning techniques in electricity load and price prediction, providing detailed analysis of methods and performance. It offers a comprehensive assessment of datasets, performance metrics, and statistical tools used in this field, and identifies prevailing challenges and future research directions.
Article
Thermodynamics
Matthias Finkenrath, Till Faber, Fabian Behrens, Stefan Leiprecht
Summary: This paper proposes a holistic modelling and optimisation approach for the efficient operation of district heating networks. It includes detailed process modelling and optimisation, numerical model for dispatch optimisation, and machine-learning-based load forecasting. The study is based on operating data from the district heating network of the city of Ulm in Germany, and identifies the potential integration of additional renewable power. The economic impact and uncertainties are also analysed using mathematical optimization and machine learning techniques.
Article
Computer Science, Artificial Intelligence
Farzaneh Tatari, Majid Mazouchi, Hamidreza Modares
Summary: This article introduces a fixed-time system identifier for continuous-time nonlinear systems, which utilizes a novel adaptive update law and concurrent learning to guarantee learning of uncertain nonlinear dynamics within a fixed time.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Energy & Fuels
J. Carlos Olives-Camps, Alvaro Rodriguez del Nozal, Juan Manuel Mauricio, Jose Maria Maza-Ortega
Summary: This paper addresses the problem of optimally operating a set of grid-forming devices in an AC microgrid without a detailed network model. The proposed control architecture consists of a local control layer and a centralized secondary controller that coordinates the setpoints of the grid-forming devices. Simulations and hardware-in-the-loop tests have validated the good performance and robustness of the proposed method under different conditions.
Article
Computer Science, Artificial Intelligence
Mohammed Ali, Rita Borgo, Mark W. Jones
Summary: The study aimed to investigate the relationship between 1D time-series data and 2D representation provided by dimension reduction techniques from a user perspective. Results showed that linking these views can positively impact speed and accuracy.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Psychology
Luke A. Rosedahl, Raina Serota, F. Gregory Ashby
Summary: This study found that verbal and written instructions significantly improved performance in rule-based category learning, but had no effect in information-integration category learning. This has important implications for teaching methods.
JOURNAL OF EXPERIMENTAL PSYCHOLOGY-HUMAN PERCEPTION AND PERFORMANCE
(2021)
Article
Psychology
Luke A. Rosedahl, F. Gregory Ashby
Summary: The study found that linear separability does not necessarily make categories easier to learn in category learning tasks, and increasing variability on irrelevant stimulus dimensions impairs information-integration learning but not rule-based learning. This suggests a novel dissociation between rule-based and information-integration category learning.
JOURNAL OF EXPERIMENTAL PSYCHOLOGY-LEARNING MEMORY AND COGNITION
(2022)
Article
Education & Educational Research
Lauren N. Jescovitch, Emily E. Scott, Jack A. Cerchiara, John Merrill, Mark Urban-Lurain, Jennifer H. Doherty, Kevin C. Haudek
Summary: This study compared two coding approaches and utilized machine learning models for undergraduate physiology constructed response assessments. Results indicated that analytic coding method performed better in more complex scenarios.
JOURNAL OF SCIENCE EDUCATION AND TECHNOLOGY
(2021)
Article
Psychology, Mathematical
Hadeer Derawi, Casey L. Roark, Yafit Gabay
Summary: Speech communication relies on accurate perception and identification of speech sounds, which is achieved through categorization. Recent research suggests that learning new speech and non-speech categories depends on the procedural learning system. Individuals with Developmental Language Disorder (DLD) have difficulties in information-integration category learning but not in rule-based category learning.
PSYCHONOMIC BULLETIN & REVIEW
(2023)
Article
Computer Science, Artificial Intelligence
Tianshan Liu, Rui Zhao, Wenqi Jia, Kin-Man Lam, Jun Kong
Summary: The popularity of wearable devices has increased the demand for first-person activity recognition. In order to analyze and recognize both first-person and third-person activities, the researchers have created a new activity dataset and proposed an integrated feature extraction and learning method. Experimental results validate that this method achieves state-of-the-art performance.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Psychology, Biological
C. E. R. Edmunds, Andy J. Wills, Fraser Milton
QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY
(2019)
Article
Psychology, Biological
Tina Seabrooke, Andy J. Wills, Lee Hogarth, Chris J. Mitchell
QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY
(2019)
Article
Linguistics
Tina Seabrooke, Timothy J. Hollins, Christopher Kent, Andy J. Wills, Chris J. Mitchell
JOURNAL OF MEMORY AND LANGUAGE
(2019)
Article
Psychology, Biological
Stuart G. Spicer, Chris J. Mitchell, Andy J. Wills, Peter M. Jones
JOURNAL OF EXPERIMENTAL PSYCHOLOGY-ANIMAL LEARNING AND COGNITION
(2020)
Article
Psychology, Biological
Fraser Milton, I. P. L. McLaren, Edward Copestake, David Satherley, Andy J. Wills
JOURNAL OF EXPERIMENTAL PSYCHOLOGY-ANIMAL LEARNING AND COGNITION
(2020)
Article
Psychology, Biological
Andy J. Wills, Lyn Ellett, Fraser Milton, Gareth Croft, Tom Beesley
LEARNING & BEHAVIOR
(2020)
Article
Psychology
Rene Schlegelmilch, Andy J. Wills, Bettina von Helversen
Summary: The Category Abstraction Learning (CAL) model describes category learning through processes of similarity-based generalization and dissimilarity-based abstraction, guided by two attention mechanisms. It explains how rules are learned from scratch and provides explanations for various learning phenomena, challenging existing theories. The model's potential lies in measuring cognitive processes regarding attention, abstraction, error detection, and memorization from multiple psychological perspectives.
PSYCHOLOGICAL REVIEW
(2022)
Article
Psychology, Experimental
Tina Seabrooke, Chris J. Mitchell, Andy J. Wills, Angus B. Inkster, Timothy J. Hollins
Summary: The research found that guessing the meanings of unknown words can improve later recognition of their meanings compared to studying alone. The error-correction hypothesis suggests that incorrect guesses can promote memory for the meanings when they are revealed. The experiments showed that guessing has a positive impact on target recognition, but not on associative recognition performance.
MEMORY & COGNITION
(2022)
Article
Neurosciences
Angus B. Inkster, Fraser Milton, Charlotte E. R. Edmunds, Abdelmalek Benattayallah, Andy J. Wills
Summary: The inverse base rate effect is a nonrational behavioral phenomenon in which participants preferentially select outcomes that are different from the base rates. Error-driven learning explains this phenomenon, with brain areas associated with prediction error playing a key role.
HUMAN BRAIN MAPPING
(2022)
Article
Psychology, Biological
Stuart G. Spicer, Chris J. Mitchell, Andy J. Wills, Katie L. Blake, Peter M. Jones
Summary: Theories of associative learning often suggest that learning is influenced by prediction error, but a recent study by Spicer et al. proposes that humans are more likely to attribute surprising outcomes to uncertain cues, in order to maintain confident cue-outcome associations. The findings from the study support this theory, and further experiments compare it to other theories and examine the role of inhibition in learning. The results show that participants learned more about cues with larger prediction errors in inhibition-based learning.
JOURNAL OF EXPERIMENTAL PSYCHOLOGY-ANIMAL LEARNING AND COGNITION
(2022)
Article
Psychology, Experimental
Timothy J. Hollins, Tina Seabrooke, Angus Inkster, Andy Wills, Chris J. Mitchell
Summary: Guessing the answer to a question before seeing the answer can improve memory, known as the pre-testing effect. This effect also occurs in general knowledge learning, where people are more likely to remember information they were curious about. However, the pre-testing effect is not consistent with a general state of curiosity.
Article
Psychology, Mathematical
Tina Seabrooke, Chris J. Mitchell, Andy J. Wills, Timothy J. Hollins
Summary: Attempting to retrieve answers during an initial test can improve memory, especially for related word pairs, even if the retrieval attempts are unsuccessful. However, such improvement is not observed for unrelated word pairs. The popular theory that the pretesting effect depends on partial activation of the target during the pretesting phase is challenged by the data.
PSYCHONOMIC BULLETIN & REVIEW
(2021)
Article
Psychology, Experimental
Tina Seabrooke, Chris J. Mitchell, Andy J. Wills, Jessica L. Waters, Timothy J. Hollins
Article
Psychology, Experimental
Charlotte E. R. Edmunds, Fraser Milton, Andy J. Wills
Article
Psychology, Experimental
Cai S. Longman, Fraser Milton, Andy J. Wills, Frederick Verbruggen
