Results 281 to 290 of about 1,311,020 (347)

WITHDRAWN: Effects of Reinforcer Type on Performance of Psychological Tasks

Neurotoxicology and Teratology, 2007
This article has been withdrawn at the request of the author(s) and/or editor. The Publisher apologizes for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at http://www.elsevier.com/locate/withdrawalpolicy.
S L, Freas, J J, Chelonis, L B, Forzano, M G, Paule   +3 more
openaire   +2 more sources

The Inadequacy of Reinforcement Learning From Human Feedback—Radicalizing Large Language Models via Semantic Vulnerabilities

IEEE Transactions on Cognitive and Developmental Systems
This study is an empirical investigation into the semantic vulnerabilities of four popular pretrained commercial large language models (LLMs) to ideological manipulation.
Timothy R. Mcintosh, Teo Sušnjak, Tong Liu, Paul A. Watters, M. Halgamuge   +4 more
semanticscholar   +1 more source

Positive Psychology and Indian Psychology In Need of Mutual Reinforcement

Psychological Studies, 2014
The current practices of positive psychology are woven into the behavioural fabric in the form of numerous strategies/practices without much theoretical foundation. Positive psychology moved from repair to reconstruction, from the negative side of human nature to its positive aspect.
openaire   +1 more source

CogBench: a large language model walks into a psychology lab

International Conference on Machine Learning
Large language models (LLMs) have significantly advanced the field of artificial intelligence. Yet, evaluating them comprehensively remains challenging.
Julian Coda-Forno, Marcel Binz, Jane X. Wang, Eric Schulz   +3 more
semanticscholar   +1 more source

Social reinforcement of somatic versus psychological description of depressive events

Behaviour Research and Therapy, 2005
The cultural construction of illness model explains the clinical observation that psychological correlates of depression such as sadness and worthlessness are frequently reported in Western cultures, whereas somatic or vegetative complaints are often associated with depression in non-Western cultures. This study employed Portnoy and Salzinger's (J. Gen.
KaNei, Lam, Christine, Marra, Kurt, Salzinger   +2 more
openaire   +2 more sources

The Role of Reinforcement Learning in Enhancing Education: Applications in Psychological Education and Intelligent Tutoring Systems

Highlights in Science Engineering and Technology
In the domains of education and psychology, Reinforcement Learning (RL), as a branch of Artificial Intelligence, is increasingly revealing its substantial potential to revolutionize educational methodologies.
Jietao Xie
semanticscholar   +1 more source

Equipping With Cognition: Interactive Motion Planning Using Metacognitive-Attribution Inspired Reinforcement Learning for Autonomous Vehicles

IEEE transactions on intelligent transportation systems (Print)
This study introduces the Metacognitive-Attribution Inspired Reinforcement Learning (MAIRL) approach, designed to address unprotected interactive left turns at intersections—one of the most challenging tasks in autonomous driving.
Xiaohui Hou, Minggang Gan, Wei Wu, Yuan Ji, Shiyue Zhao, Jie Chen   +5 more
semanticscholar   +1 more source

Clinical Psychology: Reinforcing Inequalities or Facilitating Empowerment?

The International Journal of Human Rights, 2003
To what extent do psychologists continue to reinforce inequalities by unquestioningly reaffirming existing oppressive theorising and practices, thereby maintaining the status quo and endorsing human rights violations? Or, to what extent do they attempt to facilitate empowerment by those who have suffered human rights violations, and do they challenge ...
openaire   +1 more source

Data-driven equation discovery reveals nonlinear reinforcement learning in humans

Proceedings of the National Academy of Sciences of the United States of America
Significance Our article offers an answer to a foundational question in psychology and neuroscience: how do people learn from rewards and punishments? Specifically, we introduce a computational model of human reinforcement learning (RL) that points to a ...
Kyle J. LaFollette, J. Yuval, Roey Schurr, David E. Melnikoff, Amit Goldenberg   +4 more
semanticscholar   +1 more source

CogDual: Enhancing Dual Cognition of LLMs via Reinforcement Learning with Implicit Rule-Based Rewards

Conference on Empirical Methods in Natural Language Processing
Role-Playing Language Agents (RPLAs) have emerged as a significant application direction for Large Language Models (LLMs). Existing approaches typically rely on prompt engineering or supervised fine-tuning to enable models to imitate character behaviors ...
Cheng Liu, Yifei Lu, F. Ye, Jian Li, Xingyu Chen, Feiliang Ren, Zhaopeng Tu, Xiaolong Li   +7 more
semanticscholar   +1 more source