AIMC Topic: Reward

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Biased Pressure: Cyclic Reinforcement Learning Model for Intelligent Traffic Signal Control.

Sensors (Basel, Switzerland) Apr 6, 2022
Existing inefficient traffic signal plans are causing traffic congestions in many urban areas. In recent years, many deep reinforcement learning (RL) methods have been proposed to control traffic signals in real-time by interacting with the environme...
Reward Learning Machine Learning
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Semicentralized Deep Deterministic Policy Gradient in Cooperative StarCraft Games.

IEEE transactions on neural networks and learning systems Apr 4, 2022
In this article, we propose a novel semicentralized deep deterministic policy gradient (SCDDPG) algorithm for cooperative multiagent games. Specifically, we design a two-level actor-critic structure to help the agents with interactions and cooperatio...
Neural Networks, Computer Policy Reward Learning Algorithms
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Exploration in neo-Hebbian reinforcement learning: Computational approaches to the exploration-exploitation balance with bio-inspired neural networks.

Neural networks : the official journal of the International Neural Network Society Mar 23, 2022
Recent theoretical and experimental works have connected Hebbian plasticity with the reinforcement learning (RL) paradigm, producing a class of trial-and-error learning in artificial neural networks known as neo-Hebbian plasticity. Inspired by the ro...
Neural Networks, Computer Reinforcement, Psychology Reward Learning
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Using deep learning to predict human decisions and using cognitive models to explain deep learning models.

Scientific reports Mar 18, 2022
Deep neural networks (DNNs) models have the potential to provide new insights in the study of cognitive processes, such as human decision making, due to their high capacity and data-driven design. While these models may be able to go beyond theory-dr...
Humans Decision Making Deep Learning Neural Networks, Computer Cognition Reward
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A deep reinforcement transfer convolutional neural network for rolling bearing fault diagnosis.

ISA transactions Feb 25, 2022
Deep neural networks highly depend on substantial labeled samples when identifying bearing fault. However, in some practical situations, it is very difficult to collect sufficient labeled samples, which limits the application of deep neural networks ...
Learning Neural Networks, Computer Reward Reinforcement, Psychology
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Outracing champion Gran Turismo drivers with deep reinforcement learning.

Nature Feb 9, 2022
Many potential applications of artificial intelligence involve making real-time decisions in physical systems while interacting with humans. Automobile racing represents an extreme example of these conditions; drivers must execute complex tactical ma...
Reinforcement, Psychology Video Games Automobile Driving Competitive Behavior Sports Deep Learning Reward Humans
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Toward the biological model of the hippocampus as the successor representation agent.

Bio Systems Jan 29, 2022
The hippocampus is an essential brain region for spatial memory and learning. Recently, a theoretical model of the hippocampus based on temporal difference (TD) learning has been published. Inspired by the successor representation (SR) learning algor...
Hippocampus Reward Brain Models, Biological Artificial Intelligence
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Meta-analysis of human prediction error for incentives, perception, cognition, and action.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology Jan 11, 2022
Prediction errors (PEs) are a keystone for computational neuroscience. Their association with midbrain neural firing has been confirmed across species and has inspired the construction of artificial intelligence that can outperform humans. However, t...
Artificial Intelligence Magnetic Resonance Imaging Cognition Humans Motivation Reward Perception
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Underwater gliders linear trajectory tracking: The experience breeding actor-critic approach.

ISA transactions Dec 28, 2021
This paper studies the underwater glider trajectory tracking in currents field. The objective is to ensure that trajectories fit to the straight target track. The underwater glider model is introduced to demonstrate the vehicle dynamic properties. Co...
Computer Simulation Uncertainty Reward Neural Networks, Computer
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Exploring the Black Box of Managing Total Rewards for Older Professionals in the Canadian Financial Services Sector.

Canadian journal on aging = La revue canadienne du vieillissement Dec 10, 2021
This study extends our knowledge about the management of older employees in the sector of financial services, which faces enormous transformational pressures (e.g., emergence of artificial intelligence, digital services). Based on the black box model...
Retirement Artificial Intelligence Workforce Humans Reward Canada
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