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相关概念视频

Observational Learning01:12

Observational Learning

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

Multi-input and Multi-variable systems

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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 of...
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Neural Regulation01:37

Neural Regulation

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Digestion begins with a cephalic phase that prepares the digestive system to receive food. When our brain processes visual or olfactory information about food, it triggers impulses in the cranial nerves innervating the salivary glands and stomach to prepare for food.
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Operant Conditioning Intervention01:24

Operant Conditioning Intervention

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Operant conditioning serves as a foundational principle in therapeutic interventions aimed at modifying maladaptive behaviors. Central to this approach is the notion that behaviors, both adaptive and maladaptive, are learned through reinforcement. By analyzing the environmental factors that reinforce problematic behaviors, clinicians can design interventions to weaken these reinforcements and replace maladaptive behaviors with healthier alternatives.
In operant conditioning, behaviors that are...
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Reinforcement01:23

Reinforcement

992
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:
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Neural Control of Respiration01:18

Neural Control of Respiration

5.1K
The neural regulation of respiration is a meticulously coordinated process primarily controlled by the respiratory centers located within the brainstem. These centers, composed of specialized neurons, transmit nerve impulses that control the contraction and relaxation of our respiratory muscles.
Respiratory Centers in the Brainstem
Two primary areas comprise the respiratory center: the medullary respiratory center in the medulla oblongata and the pontine respiratory group in the pons. The...
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A Fully Automated Rodent Conditioning Protocol for Sensorimotor Integration and Cognitive Control Experiments
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深度强化学习用于干预部分可观测的监管网络.

Seyed Hamid Hosseini1, Mahdi Imani1

  • 1Department of Electrical and Computer Engineering at Northeastern University.

Proceedings of the ... American Control Conference. American Control Conference
|February 23, 2026
PubMed
概括

这项研究引入了一个深度强化学习框架,用于优化在基因调节网络 (GRNs) 中进行干预的不完整数据. 该方法有效地管理不确定性以控制基因活性,优于现有的方法.

科学领域:

  • 计算生物学 计算生物学
  • 系统生物学 系统生物学
  • 生物信息学是一种生物信息学.

背景情况:

  • 基因调节网络 (GRNs) 控制细胞功能.
  • 现实世界的GRN分析受到部分可观测性和噪音数据的挑战.
  • 现有的干预方法通常假定完整的系统状态信息.

研究的目的:

  • 开发一个深度强化学习框架,用于在部分可观测的GRNs中制定最佳干预政策.
  • 为了解决假定完全可观测性的现有方法的局限性.
  • 为了管理基因表达数据和基因活动随机性的不确定性.

主要方法:

  • 扩展布尔网络模型以包含部分可观测性.
  • 在信念空间中制定最佳干预策略,利用信念状态来表示状态后部分布.
  • 应用深度Q网络 (DQN) 以可扩展的方式接近最佳政策.
  • 在降低不确定性条件下,分析证明了对最佳动态编程解决方案的趋同.

主要成果:

  • 拟议的深度强化学习框架有效地处理GRNs中的部分可观测性.
  • 信念状态成功地捕获了数据不确定性和基因活动随机性.
  • 与现有方法相比,对黑色素瘤GRN进行的数值实验显示,在维持所需状态和减少与癌症相关的基因激活方面,性能有所改善.

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结论:

  • 开发的框架为设计复杂,部分可观测的生物系统的干预策略提供了一个强大的方法.
  • 深度强化学习为优化GRN干预提供了一个可扩展的解决方案.
  • 该方法有望通过向特定的基因调节通路,在精密医学和疾病控制领域应用.