AIMC Topic: Reward

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Offline reward shaping with scaling human preference feedback for deep reinforcement learning.

Neural networks : the official journal of the International Neural Network Society Nov 1, 2024
Designing reward functions that fully align with human intent is often challenging. Preference-based Reinforcement Learning (PbRL) provides a framework where humans can select preferred segments through pairwise comparisons of behavior trajectory seg...
Humans Neural Networks, Computer Reward Reinforcement, Psychology Choice Behavior Deep Learning Robotics
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Highly valued subgoal generation for efficient goal-conditioned reinforcement learning.

Neural networks : the official journal of the International Neural Network Society Oct 28, 2024
Goal-conditioned reinforcement learning is widely used in robot control, manipulating the robot to accomplish specific tasks by maximizing accumulated rewards. However, the useful reward signal is only received when the desired goal is reached, leadi...
Goals Reinforcement, Psychology Algorithms Humans Learning Robotics Neural Networks, Computer Reward
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Learning explainable task-relevant state representation for model-free deep reinforcement learning.

Neural networks : the official journal of the International Neural Network Society Sep 20, 2024
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 ...
Deep Learning Decision Making Humans Neural Networks, Computer Reward Reinforcement, Psychology
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Exploring the effectiveness of reward-based learning strategies for second-language speech sounds.

Psychonomic bulletin & review Aug 7, 2024
Adults struggle to learn non-native speech categories in many experimental settings (Goto, Neuropsychologia, 9(3), 317-323 1971), but learn efficiently in a video game paradigm where non-native speech sounds have functional significance (Lim & Holt, ...
Multilingualism Reinforcement, Psychology Speech Perception Phonetics Learning Adult Deep Learning Reward Humans
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Emergence of integrated behaviors through direct optimization for homeostasis.

Neural networks : the official journal of the International Neural Network Society May 8, 2024
Homeostasis is a self-regulatory process, wherein an organism maintains a specific internal physiological state. Homeostatic reinforcement learning (RL) is a framework recently proposed in computational neuroscience to explain animal behavior. Homeos...
Reinforcement, Psychology Reward Homeostasis Humans Neural Networks, Computer Animals Robotics
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Salience Interest Option: Temporal abstraction with salience interest functions.

Neural networks : the official journal of the International Neural Network Society Apr 25, 2024
Reinforcement Learning (RL) is a significant machine learning subfield that emphasizes learning actions based on environment to obtain optimal behavior policy. RL agents can make decisions at variable time scales in the form of temporal abstractions,...
Humans Neural Networks, Computer Machine Learning Algorithms Time Factors Reward Decision Making Reinforcement, Psychology
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Distributed deep reinforcement learning based on bi-objective framework for multi-robot formation.

Neural networks : the official journal of the International Neural Network Society Dec 1, 2023
Improving generalization ability in multi-robot formation can reduce repetitive training and calculation. In this paper, we study the multi-robot formation problem with the ability to generalize the target position. Since the generalization ability o...
Reward Reinforcement, Psychology Learning Algorithms Robotics
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Artificial intelligence and assistive technology: risks, rewards, challenges, and opportunities.

Assistive technology : the official journal of RESNA Sep 25, 2023
Humans Self-Help Devices Artificial Intelligence Reward
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Anthropomorphism-based causal and responsibility attributions to robots.

Scientific reports Jul 28, 2023
People tend to expect mental capabilities in a robot based on anthropomorphism and often attribute the cause and responsibility for a failure in human-robot interactions to the robot. This study investigated the relationship between mind perception, ...
Social Behavior Social Perception Robotics Humans Reward Emotions
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Deep Reinforcement Learning on Autonomous Driving Policy With Auxiliary Critic Network.

IEEE transactions on neural networks and learning systems Jul 6, 2023
Deep reinforcement learning (DRL) is a machine learning method based on rewards, which can be extended to solve some complex and realistic decision-making problems. Autonomous driving needs to deal with a variety of complex and changeable traffic sce...
Reinforcement, Psychology Policy Reward Neural Networks, Computer Machine Learning
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