AIMC Topic: Reward

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Artificial intelligence and assistive technology: risks, rewards, challenges, and opportunities.

Assistive technology : the official journal of RESNA Sep 25, 2023
Reward Self-Help Devices Artificial Intelligence Humans
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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, ...
Humans Emotions Social Perception Robotics Reward Social Behavior
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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...
Reward Reinforcement, Psychology Policy Machine Learning Neural Networks, Computer
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Improved Robot Path Planning Method Based on Deep Reinforcement Learning.

Sensors (Basel, Switzerland) Jun 15, 2023
With the advancement of robotics, the field of path planning is currently experiencing a period of prosperity. Researchers strive to address this nonlinear problem and have achieved remarkable results through the implementation of the Deep Reinforcem...
Intelligence Reward Robotics Acceleration Algorithms
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Preschoolers search longer when there is more information to be gained.

Developmental science May 21, 2023
What drives children to explore and learn when external rewards are uncertain or absent? Across three studies, we tested whether information gain itself acts as an internal reward and suffices to motivate children's actions. We measured 24-56-month-o...
Child Uncertainty Learning Exploratory Behavior Humans Artificial Intelligence Reward
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A reinforcement learning algorithm acquires demonstration from the training agent by dividing the task space.

Neural networks : the official journal of the International Neural Network Society May 5, 2023
Although reinforcement learning (RL) has made numerous breakthroughs in recent years, addressing reward-sparse environments remains challenging and requires further exploration. Many studies improve the performance of the agents by introducing the st...
Reward Reinforcement, Psychology Artificial Intelligence Algorithms
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De novo drug design based on Stack-RNN with multi-objective reward-weighted sum and reinforcement learning.

Journal of molecular modeling Mar 30, 2023
CONTEXT: In recent decades, drug development has become extremely important as different new diseases have emerged. However, drug discovery is a long and complex process with a very low success rate, and methods are needed to improve the efficiency o...
Neural Networks, Computer Drug Discovery Drug Design Reward
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Memristor Neural Network Circuit Based on Operant Conditioning With Immediacy and Satiety.

IEEE transactions on biomedical circuits and systems Feb 14, 2023
Most of the operant conditioning only consider the basic theory, but the influencing factors such as immediacy and satiety are ignored. In this paper, a memristor neural network circuit based on operant conditioning with immediacy and satiety is prop...
Neural Networks, Computer Brain Reward Synapses Conditioning, Operant
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Deep Deterministic Policy Gradient-Based Autonomous Driving for Mobile Robots in Sparse Reward Environments.

Sensors (Basel, Switzerland) Dec 7, 2022
In this paper, we propose a deep deterministic policy gradient (DDPG)-based path-planning method for mobile robots by applying the hindsight experience replay (HER) technique to overcome the performance degradation resulting from sparse reward proble...
Computer Simulation Robotics Reward Automobile Driving Policy
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Tuning Convolutional Spiking Neural Network With Biologically Plausible Reward Propagation.

IEEE transactions on neural networks and learning systems Nov 30, 2022
Spiking neural networks (SNNs) contain more biologically realistic structures and biologically inspired learning principles than those in standard artificial neural networks (ANNs). SNNs are considered the third generation of ANNs, powerful on the ro...
Neurons Neural Networks, Computer Algorithms Reward Models, Neurological
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