相关实验视频

Updated: Jul 23, 2025

The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

9.4K

在图形游戏中通过强化学习实现异质多代理系统的基于数据的最佳同步

Chunping Xiong, Qian Ma, Jian Guo

    IEEE transactions on neural networks and learning systems
    |July 18, 2023
    PubMed
    概括

    这项研究使用先进的强化学习实现了对线性异质多代理系统 (MAS) 的最佳同步. 拟议的数据驱动方法确保代理达到同步状态,同时最大限度地降低性能指数,即使是未知的系统动态.

    更多相关视频

    Combining Computer Game-Based Behavioural Experiments With High-Density EEG and Infrared Gaze Tracking13:40

    Combining Computer Game-Based Behavioural Experiments With High-Density EEG and Infrared Gaze Tracking

    Published on: December 16, 2010

    16.8K
    Automated Interactive Video Playback for Studies of Animal Communication07:21

    Automated Interactive Video Playback for Studies of Animal Communication

    Published on: February 9, 2011

    13.6K

    相关概念视频

    Reinforcement Schedules01:24

    Reinforcement Schedules

    Positive reinforcement is a powerful method for teaching new behaviors to both animals and humans. B.F. Skinner demonstrated this with his experiments using rats in a Skinner box. When a rat pressed a lever, it received a food pellet. This immediate reward encouraged the rat to repeat the behavior. This method, where a reward follows every instance of the behavior, is known as continuous reinforcement. It is highly effective for establishing new behaviors quickly.
    Once a behavior is learned,...
    205
    Reinforcement01:23

    Reinforcement

    Positive and negative reinforcement are key concepts in operant conditioning, a learning process where the consequences of a behavior affect the likelihood of that behavior being repeated.
    Positive reinforcement occurs when a behavior is followed by the presentation of a rewarding stimulus, increasing the frequency of that behavior. For example:
    280
    Multi-input and Multi-variable systems01:22

    Multi-input and Multi-variable systems

    Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
    In the absence...
    132
    Collisions in Multiple Dimensions: Problem Solving01:06

    Collisions in Multiple Dimensions: Problem Solving

    In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
    A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
    4.3K
    Observational Learning01:12

    Observational Learning

    Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
    213
    Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

    Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

    Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
    In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
    81