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相关概念视频

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
Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

1.7K
Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...
1.7K
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
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
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
Predator-Prey Interactions02:39

Predator-Prey Interactions

16.0K
Predators consume prey for energy. Predators that acquire prey and prey that avoid predation both increase their chances of survival and reproduction (i.e., fitness). Routine predator-prey interactions elicit mutual adaptations that improve predator offenses, such as claws, teeth, and speed, as well as prey defenses, including crypsis, aposematism, and mimicry. Thus, predator-prey interactions resemble an evolutionary arms race.
16.0K

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相关实验视频

Updated: May 24, 2025

The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies
08:24

The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies

Published on: August 25, 2023

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多通道游戏中的支付控制:影响对手学习进化的影响

Juan Shi, Chen Chu, Guoxi Fan

    IEEE transactions on cybernetics
    |March 3, 2025
    PubMed
    概括

    本研究介绍了用于多道学习环境的回报控制策略. 这些策略使代理商能够绑定对手的回报,并引导学习到经过实验确认的所需平衡.

    科学领域:

    • 人工智能的人工智能
    • 游戏理论 游戏理论
    • 多代理系统 多代理系统

    背景情况:

    • 代理人在多通道环境中互动,每个通道都是重复的正常形式游戏.
    • 控制对手的回报是具有挑战性的,特别是强化学习代理.

    研究的目的:

    • 介绍多道学习中回报控制的新理论.
    • 制定策略,通过多个道将对手的预期回报绑定起来.

    主要方法:

    • 提出部分和全部回报控制策略.
    • 通过解决不平等系统来证明战略的存在.
    • 分析战略可行性的条件.

    主要成果:

    • 证明代理可以影响对手的学习进化.
    • 展示控制策略可以将学习指向所需的可行平衡.
    • 在多种多道环境中进行实验验证.

    结论:

    • 提议的回报控制理论在多道学习中是有效的.
    • 部分和完全控制策略为影响多代理学习结果提供了可行的方法.

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