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相关概念视频

Observational Learning01:12

Observational Learning

1.1K
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...
1.1K
Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

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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...
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Associative Learning01:27

Associative Learning

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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...
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Cognitive Learning01:21

Cognitive Learning

1.5K
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...
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A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
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具有社会意识导航的自主机器人使用记忆辅助深度强化学习学习.

Estrella Montero1, Nabih Pico2,3, Manuel S Alvarez-Alvarado4

  • 1Department of Electrical and Computer Engineering, Sungkyunkwan University, Natural Sciences Campus, Suwon, South Korea.

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本研究介绍了自适应机器人安全算法 (ARSA),这是一种深度强化学习方法,可以提高机器人在拥挤的空间中的机器人导航. 通过记忆辅助决策,ARSA提高了成功率,减少了导航时间,同时确保了安全.

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科学领域:

  • 机器人技术 机器人技术 机器人技术
  • 人工智能的人工智能
  • 人与机器人的交互

背景情况:

  • 在人类环境中服务机器人的成功取决于灵活的导航.
  • 人类在拥挤的空间中的随机性和活力挑战了机器人导航.
  • 现有的方法与动态的人类行为作斗争.

研究的目的:

  • 为以人为中心的环境中服务机器人开发强大的导航系统.
  • 通过深度强化学习来应对动态人类行为的挑战.
  • 通过优先考虑人类互动和安全,增强机器人的决策能力.

主要方法:

  • 实施了一种深度强化学习方法,称为自适应机器人安全算法 (ARSA).
  • 集成的双向封闭反复单元层,用于长期环境记忆.
  • 集成的动态预警区和优先考虑的人类行为在学习政策中.

主要成果:

  • 在模拟中,ARSA政策提高了4%的成功率.
  • 保持碰撞率低于4%,航行时间缩短了14%.
  • 通过现实世界的实验验证,显示流,无碰撞的导航.

结论:

  • 在动态的人类环境中,ARSA框架为机器人导航提供了卓越的效率和安全性.
  • 记忆辅助的深度强化学习有效地处理环境随机性.
  • ARSA使机器人能够主动和知情地做出决定,从而实现更安全的人机交互.