AIMC Topic: Decision Making

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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 ...

Applying a community-engaged participatory machine learning model.

American journal of community psychology
Although predictive algorithms have been described as the definitive solution to bias in health care, machine learning techniques may also propagate existing health inequities within the community context. However, there may be ways in which machine ...

Is artificial intelligence for medical professionals serving the patients?  : Protocol for a systematic review on patient-relevant benefits and harms of algorithmic decision-making.

Systematic reviews
BACKGROUND: Algorithmic decision-making (ADM) utilises algorithms to collect and process data and develop models to make or support decisions. Advances in artificial intelligence (AI) have led to the development of support systems that can be superio...

Using recurrent neural network to estimate irreducible stochasticity in human choice behavior.

eLife
Theoretical computational models are widely used to describe latent cognitive processes. However, these models do not equally explain data across participants, with some individuals showing a bigger predictive gap than others. In the current study, w...

Overtrust in AI Recommendations About Whether or Not to Kill: Evidence from Two Human-Robot Interaction Studies.

Scientific reports
This research explores prospective determinants of trust in the recommendations of artificial agents regarding decisions to kill, using a novel visual challenge paradigm simulating threat-identification (enemy combatants vs. civilians) under uncertai...