AIMC Topic: Decision Making

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Dual-hesitant fermatean fuzzy Hamacher aggregation operators and TOPSIS with their application to multi-criteria decision-making.

PloS one
The concept of the Dual-hesitant fermatean fuzzy set (DHFFS) represents a significant advancement in practical implementation, combining Fermatean fuzzy sets and Dual-hesitant sets. This new structure uses membership and non-membership hesitancy and ...

A novel approach to decision making in rice quality management using interval-valued Pythagorean fuzzy Schweizer and Sklar power aggregation operators.

PloS one
The Pythagorean fuzzy set and interval-valued intuitionistic fuzzy set are the basis of the interval-valued Pythagorean fuzzy set (IVPFS) which offers an effective approach to addressing the complex uncertainty in decision-analysis processes, making ...

Generative artificial intelligence (GenAI) and decision-making: Legal & ethical hurdles for implementation in mental health.

International journal of law and psychiatry
This article argues that significant risks are being taken with using GenAI in mental health that should be assessed urgently. It recommends that guidelines for using generative artificial intelligence (GenAI) in mental health care must be establishe...

People's judgments of humans and robots in a classic moral dilemma.

Cognition
How do ordinary people evaluate robots that make morally significant decisions? Previous work has found both equal and different evaluations, and different ones in either direction. In 13 studies (N = 7670), we asked people to evaluate humans and rob...

Wee1 inhibitor optimization through deep-learning-driven decision making.

European journal of medicinal chemistry
Deep learning has gained increasing attention in recent years, yielding promising results in hit screening and molecular optimization. Herein, we employed an efficient strategy based on multiple deep learning techniques to optimize Wee1 inhibitors, w...

HiMul-LGG: A hierarchical decision fusion-based local-global graph neural network for multimodal emotion recognition in conversation.

Neural networks : the official journal of the International Neural Network Society
Emotion recognition in conversation (ERC) is a vital task that requires deciphering human emotions through analysis of contextual and multimodal information. However, extant research on ERC concentrates predominantly on investigating multimodal fusio...

AI-induced indifference: Unfair AI reduces prosociality.

Cognition
The growing prevalence of artificial intelligence (AI) in our lives has brought the impact of AI-based decisions on human judgments to the forefront of academic scholarship and public debate. Despite growth in research on people's receptivity towards...

Learning explainable task-relevant state representation for model-free deep reinforcement learning.

Neural networks : the official journal of the International Neural Network Society
State representations considerably accelerate learning speed and improve data efficiency for deep reinforcement learning (DRL), especially for visual tasks. Task-relevant state representations could focus on features relevant to the task, filter out ...

Efficient visual representations for learning and decision making.

Psychological review
The efficient representation of visual information is essential for learning and decision making due to the complexity and uncertainty of the world, as well as inherent constraints on the capacity of cognitive systems. We hypothesize that biological ...

Elements of episodic memory: insights from artificial agents.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Many recent artificial intelligence (AI) systems take inspiration from biological episodic memory. Here, we ask how these 'episodic-inspired' AI systems might inform our understanding of biological episodic memory. We discuss work showing that these ...