AIMC Topic: Reinforcement, Psychology

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Autoshaped choice in artificial neural networks: implications for behavioral economics and neuroeconomics.

Behavioural processes Feb 4, 2015
An existing neural network model of conditioning was used to simulate autoshaped choice. In this phenomenon, pigeons first receive an autoshaping procedure with two keylight stimuli X and Y separately paired with food in a forward-delay manner, inter...
Animals Behavior, Animal Economics, Behavioral Columbidae Reinforcement, Psychology Neural Networks, Computer Choice Behavior Computer Simulation
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Application of Reinforcement Learning Algorithms for the Adaptive Computation of the Smoothing Parameter for Probabilistic Neural Network.

IEEE transactions on neural networks and learning systems Dec 19, 2014
In this paper, we propose new methods for the choice and adaptation of the smoothing parameter of the probabilistic neural network (PNN). These methods are based on three reinforcement learning algorithms: Q(0)-learning, Q(λ)-learning, and stateless ...
Algorithms Models, Theoretical Humans Neural Networks, Computer Probability Reinforcement, Psychology
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DRL-driven padel players: Simulating padel matches through deep reinforcement learning in real and hypothetical scenarios.

Journal of sports sciences Sep 1, 2025
Recent advances in Deep Reinforcement Learning (DRL) have opened new avenues for sport research. DRL allows virtual agents to learn and solve complex tasks with minimal input, which means that models can be trained with little or no data collection. ...
Reinforcement, Psychology Reinforcement Machine Learning Humans Computer Simulation Robotics Athletic Performance Deep Learning
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Multi-agent self-attention reinforcement learning for multi-USV hunting target.

Neural networks : the official journal of the International Neural Network Society Sep 1, 2025
A reinforcement learning (RL) method based on the multi-head self-attention (MSA) mechanism is proposed to solve the challenge of multiple unmanned surface vehicles (multi-USV) hunting target at the surface. The kinematic, dynamic, and environmental ...
Attention Reinforcement, Psychology Algorithms Humans Robotics Neural Networks, Computer
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Model-free reinforcement learning control with zero-min barrier functions for constrained systems.

Neural networks : the official journal of the International Neural Network Society Sep 1, 2025
The primary focus of this research is to develop an adaptive output feedback controller designed to minimize a cost-to-go function subject to constraints on input, output, and tracking error for a class of unknown non-affine discrete-time systems. Th...
Humans Neural Networks, Computer Feedback Fuzzy Logic Reinforcement, Psychology Machine Learning Algorithms
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Comparing Deterministic and Stochastic Reinforcement Learning for Glucose Regulation in Type 1 Diabetes.

Studies in health technology and informatics Aug 7, 2025
Type 1 Diabetes (T1D) is a chronic condition affecting millions worldwide, requiring external insulin administration to regulate blood glucose levels and prevent serious complications. Artificial Pancreas Systems (APS) for managing T1D currently rely...
Adolescent Blood Glucose Computer Simulation Adult Stochastic Processes Machine Learning Reinforcement, Psychology Algorithms Pancreas, Artificial Insulin Humans Diabetes Mellitus, Type 1
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Rethinking exploration-exploitation trade-off in reinforcement learning via cognitive consistency.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
The exploration-exploitation dilemma is one of the fundamental challenges in deep reinforcement learning (RL). Agents must strike a trade-off between making decisions based on current beliefs or gathering more information. Prior work mostly prefers d...
Neural Networks, Computer Deep Learning Decision Making Reward Cognition Reinforcement, Psychology Humans
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HCPI-HRL: Human Causal Perception and Inference-driven Hierarchical Reinforcement Learning.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
The dependency on extensive expert knowledge for defining subgoals in hierarchical reinforcement learning (HRL) restricts the training efficiency and adaptability of HRL agents in complex, dynamic environments. Inspired by human-guided causal discove...
Reward Perception Neural Networks, Computer Reinforcement, Psychology Humans Algorithms
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Episodic Memory-Double Actor-Critic Twin Delayed Deep Deterministic Policy Gradient.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Existing deep reinforcement learning (DRL) algorithms suffer from the problem of low sample efficiency. Episodic memory allows DRL algorithms to remember and use past experiences with high return, thereby improving sample efficiency. However, due to ...
Reinforcement, Psychology Reward Memory, Episodic Humans Algorithms Deep Learning
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Heterogeneity, reinforcement learning, and chaos in population games.

Proceedings of the National Academy of Sciences of the United States of America Jun 24, 2025
Inspired by the challenges at the intersection of Evolutionary Game Theory and Machine Learning, we investigate a class of discrete-time multiagent reinforcement learning (MARL) dynamics in population/nonatomic congestion games, where agents have div...
Reinforcement, Psychology Game Theory Learning Nonlinear Dynamics Humans Machine Learning
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