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相关概念视频

Modeling in Therapy01:26

Modeling in Therapy

120
Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in...
120
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

81
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
Reinforcement01:23

Reinforcement

277
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:
277
Observational Learning01:12

Observational Learning

210
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...
210
Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

1.8K
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...
1.8K
Steps in the Modeling Process01:14

Steps in the Modeling Process

241
Albert Bandura's theory of observational learning identifies four critical processes: attention, retention, motor reproduction, and reinforcement or motivation.
Attention is the first necessary component for observational learning. It involves focusing on what the model is doing and saying. For example, if you decide to take a drawing class to enhance your skills, you need to pay close attention to the instructor's words and hand movements. The characteristics of the model significantly...
241

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相关实验视频

Updated: Jul 19, 2025

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents
07:05

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents

Published on: September 10, 2018

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在不确定性下的业务流程的建模和预测监测与强化学习.

Alexandros Bousdekis1, Athanasios Kerasiotis1, Silvester Kotsias1

  • 1Department of Informatics and Computer Engineering, University of West Attica, 12242 Egaleo, Greece.

Sensors (Basel, Switzerland)
|August 12, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了用于预测业务流程监控的强化学习 (RL),解决了传统过程采矿的复杂性和决定性限制. 这种新的方法增强了过程分析和预测能力.

关键词:
业务流程管理 业务流程管理数据分析数据分析.机器学习是机器学习.预测性业务流程监控,监控业务流程.过程采矿过程采矿

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相关实验视频

Last Updated: Jul 19, 2025

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents
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科学领域:

  • 计算机科学 计算机科学
  • 人工智能的人工智能
  • 业务流程管理 业务流程管理

背景情况:

  • 过程挖掘从事件日志分析业务流程,以发现,监控和改进它们.
  • 传统的过程发现方法产生复杂的,难以理解的模型,由于其决定性性质,缺乏预测能力.
  • 现有的方法与不确定性作斗争,无法预测未来的过程行为.

研究的目的:

  • 开发一种新的预测性业务流程监控方法.
  • 利用强化学习 (RL) 进行增强的过程分析和预测.
  • 解决传统过程采矿在处理复杂性和不确定性方面的局限性.

主要方法:

  • 利用强化学习 (RL) 技术进行预测过程监控.
  • 开发了一种新的方法来建模和预测业务流程行为.
  • 在银行部门使用实际用例评估拟议的方法.

主要成果:

  • 证明了用于预测业务流程监控的强化学习的可行性.
  • 提出的基于RL的方法为传统方法的复杂性和决定性限制提供了潜在的解决方案.
  • 银行业的用例提供了对该方法的实际应用和有效性的见解.

结论:

  • 强化学习为推进预测业务流程监控提供了一个有希望的途径.
  • 开发的方法可能会导致更易于理解和预测的过程模型.
  • 在这个领域进行进一步的研究可以显著提高业务流程管理和运营效率.