AIMC Topic: Reward

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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...
Algorithms Robotics Intelligence Reward Acceleration
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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...
Humans Artificial Intelligence Learning Child Reward Exploratory Behavior Uncertainty
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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...
Artificial Intelligence Algorithms Reward Reinforcement, Psychology
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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 Design Drug Discovery 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 Policy Robotics Reward Automobile Driving
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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...
Neural Networks, Computer Algorithms Models, Neurological Neurons Reward
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Goals, usefulness and abstraction in value-based choice.

Trends in cognitive sciences Nov 26, 2022
Colombian drug lord Pablo Escobar, while on the run, purportedly burned two million dollars in banknotes to keep his daughter warm. A stark reminder that, in life, circumstances and goals can quickly change, forcing us to reassess and modify our valu...
Artificial Intelligence Brain Decision Making Brain Mapping Reward Goals Choice Behavior
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Robust Inverse Q-Learning for Continuous-Time Linear Systems in Adversarial Environments.

IEEE transactions on cybernetics Nov 18, 2022
This article proposes robust inverse Q -learning algorithms for a learner to mimic an expert's states and control inputs in the imitation learning problem. These two agents have different adversarial disturbances. To do the imitation, the learner mus...
Neural Networks, Computer Algorithms Reward
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Deep Reinforcement Learning for the Detection of Abnormal Data in Smart Meters.

Sensors (Basel, Switzerland) Nov 6, 2022
The rapidly growing power data in smart grids have created difficulties in security management. The processing of large-scale power data with the use of artificial intelligence methods has become a hotspot research topic. Considering the early warnin...
Artificial Intelligence Algorithms Reward Reinforcement, Psychology
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