Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Reinforcement01:23

Reinforcement

172
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:
172
Cognitive Learning01:21

Cognitive Learning

144
Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
144
Observational Learning01:12

Observational Learning

118
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...
118
Associative Learning01:27

Associative Learning

276
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
276
Reinforcement Schedules01:24

Reinforcement Schedules

126
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,...
126
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

93
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...
93

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Cross-sector deep learning scales life cycle assessment using unified textual descriptions.

Environmental science and ecotechnology·2026
Same author

[Retracted] Acaricidal activity of extracts from <i>Ligularia virgaurea</i> against the <i>Sarcoptes scabiei</i> mite <i>in vitro</i>.

Experimental and therapeutic medicine·2026
Same author

Redefining Photoinitiator Risk Prioritization by Bridging Environmental Fate and Human Internal Exposure.

Environmental science & technology·2026
Same author

Reinterpreting diffusive constraints: Concentration cloaking via homogenization and pseudoconformal mapping.

Physical review. E·2026
Same author

Recent Advances on Off-Policy Reinforcement Learning for Optimization Control.

IEEE transactions on cybernetics·2026
Same author

Efficacy of tranexamic acid combined with octreotide in acute upper gastrointestinal bleeding: A retrospective clinical controlled study of high-risk patients.

Pakistan journal of pharmaceutical sciences·2026
Same journal

Intervention Feasible Region and Driver Risk Capacity Aware Human-Machine Collaborative Safe Trajectory Planning.

IEEE transactions on neural networks and learning systems·2026
Same journal

A Unified Differential Denoising Learning Framework With a Pre-Trained Model and Fuzzy Graph Networks for Drug-Drug Interaction Prediction.

IEEE transactions on neural networks and learning systems·2026
Same journal

Self-Supervised Continuous Dynamic Graph Representation Learning via Hawkes Processes.

IEEE transactions on neural networks and learning systems·2026
Same journal

cPU: Consistent Risk Estimator for Positive-Unlabeled Learning.

IEEE transactions on neural networks and learning systems·2026
Same journal

Tuning-Free Latent Diffusion Models for Ultrahigh-Resolution Image Editing.

IEEE transactions on neural networks and learning systems·2026
Same journal

Hidden Data Recovery and Forecasting via Next-Generation Reservoir Computing With Multiscale Delay Selection.

IEEE transactions on neural networks and learning systems·2026
查看所有相关文章

相关实验视频

Updated: May 24, 2025

Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device ALDM Test Systems
08:42

Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device ALDM Test Systems

Published on: May 5, 2015

12.0K

以认知为导向的多代理增强学习学习.

Tenghai Qiu, Shiguang Wu, Zhen Liu

    IEEE transactions on neural networks and learning systems
    |March 3, 2025
    PubMed
    概括
    此摘要是机器生成的。

    这项研究引入了一个新的认知导向的多代理强化学习 (CORL) 框架. 通过使用局部观察来提高情境和自我认知,提高团队协调,CORL提高了代理合作和绩效.

    更多相关视频

    A Fully Automated and Highly Versatile System for Testing Multi-cognitive Functions and Recording Neuronal Activities in Rodents
    09:13

    A Fully Automated and Highly Versatile System for Testing Multi-cognitive Functions and Recording Neuronal Activities in Rodents

    Published on: May 3, 2012

    14.3K
    A Fully Automated Rodent Conditioning Protocol for Sensorimotor Integration and Cognitive Control Experiments
    09:43

    A Fully Automated Rodent Conditioning Protocol for Sensorimotor Integration and Cognitive Control Experiments

    Published on: April 15, 2014

    10.5K

    相关实验视频

    Last Updated: May 24, 2025

    Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device ALDM Test Systems
    08:42

    Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device ALDM Test Systems

    Published on: May 5, 2015

    12.0K
    A Fully Automated and Highly Versatile System for Testing Multi-cognitive Functions and Recording Neuronal Activities in Rodents
    09:13

    A Fully Automated and Highly Versatile System for Testing Multi-cognitive Functions and Recording Neuronal Activities in Rodents

    Published on: May 3, 2012

    14.3K
    A Fully Automated Rodent Conditioning Protocol for Sensorimotor Integration and Cognitive Control Experiments
    09:43

    A Fully Automated Rodent Conditioning Protocol for Sensorimotor Integration and Cognitive Control Experiments

    Published on: April 15, 2014

    10.5K

    科学领域:

    • 人工智能的人工智能
    • 机器学习 机器学习
    • 认知科学 认知科学

    背景情况:

    • 多代理强化学习 (MARL) 常常在使用局部观察时,难以进行有效的合作.
    • 对个体行为的心理洞察力可以为MARL中的代理认知提供信息.
    • 现有的MARL框架可能缺乏准确的角色差异化和团队协调机制.

    研究的目的:

    • 提出一种新的以认知为导向的多代理强化学习 (CORL) 框架.
    • 通过利用本地观察来加强MARL任务中的代理合作和绩效.
    • 通过先进的认知机制来改善团队协调和角色差异化.

    主要方法:

    • 开发了一个CORL框架,为代理人提供基于当地观察得出的情境和自我认知.
    • 引入了两个信息理论规范器,以增强认知信息性和精度.
    • 采用了政策网络培训的集中培训与分散执行 (CTDE) 框架.

    主要成果:

    • 科尔 (CORL) 证明了有效地利用当地观测数据来加强合作.
    • 观察到显著的性能改善,特别是在具有挑战性的多代理任务中.
    • 拟议的调节剂改善了局势认知与全球状态的调整,以及与代理身份的自我认知.

    结论:

    • CORL框架提供了一个有前途的方法来加强合作在多代理强化学习.
    • 利用心理洞察力和信息理论调节器可以显著提高代理商的性能.
    • 在复杂的MARL场景中,CORL提供了一种可靠的方法,以改善角色差异化和团队协调.