Kastalia Knowledge Management System · Glasperlenspiel template · knot 1517
Human and Machine Learning
Ancestors (3 superordinated paths)
Descendants (at least 46 branches originate here)
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Human and Machine Learning
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is_parent Homo discens
"Man is a 'homo discens,' a learning being. People learn as long as they live. Life is inseparably connected with learning." Horst Siebert -
is_parent Implicit learning
Implicit learning is the process of acquiring knowledge or skills unconsciously, without intentional effort or explicit awareness of what is being learned. It t-
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Observation
Observation in the context of learning refers to the process of acquiring knowledge, skills, or behaviors by perceiving the actions of others or the dynamics wi -
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Unsupervised learning
Unsupervised learning is a type of machine learning where a model is trained on data without labeled outcomes. The system analyzes and identifies patterns or st -
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Imitation
Imitation in humans, especially in children, is the process of learning by observing and replicating the actions, behaviors, or expressions of others. It is a f -
is_parent Features of implicit learning ·
No direct guidance :: Learner L must identify patterns or relationships from raw input on her own. Pattern discovery :: Observation often involves recognizing a -
is_parent 1st definition of learning ·
Learning is building A model of THE world.
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is_parent Experiential learning
Experiential learning is a process of learning through direct experience, where individuals engage in activities, reflect on their actions, and apply what they’-
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Trial
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In learning and problem-solving, a "trial" is a single attempt or effort to reach a goal or find a solution. Each trial involves testing an idea or making a cha -
is_parent Repetition
In learning, skill-building, and habit formation, repetition is the process of repeatedly practicing or performing a task. This continuous repetition reinforces -
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Error
In learning and problem-solving, an "error" is the difference between what we aimed to achieve and the actual result. It shows how far we are from the desired o -
is_parent Game
Game provides a closed system whereby we are allowed to commit errors (& learn from them) without major consequences for real life. What is Your most favori
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is_parent Supervised learning 🔊
Supervised learning is a type of machine learning where a model is trained on labeled data to learn the mapping between input features and corresponding outputs-
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Classifiers
A classifier in machine learning is a model or algorithm designed to categorize data into predefined groups or labels. It takes input data, analyzes its feature -
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Training
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In supervised machine learning, training is the process of teaching a model, like a classifier, to make accurate predictions by learning patterns from labeled d -
is_parent Validating ·
In supervised machine learning, *validating* is the process of fine-tuning and assessing a model's performance during training to ensure it generalizes well to -
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Testing ·
In supervised machine learning, *testing* (or *inference*) is the process of evaluating a trained model's ability to make accurate predictions on new, unseen da -
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Evaluation
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Binary classifiers are evaluated by comparing their predictions to the actual outcomes using a confusion matrix. This is a table with four categories: True Posi -
is_parent Supervised learning & Human learning
Supervised learning parallels human learning through its reliance on guidance from labeled examples, similar to how humans learn with feedback. For instance, wh
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Reinforcement learning
Reinforcement learning (RL) is a machine learning paradigm where an agent learns to make decisions by interacting with an environment. Instead of being told wha-
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From supervised to reinforcement learning
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Supervised learning resembles a structured classroom environment, where explicit feedback is given for each example (e.g., a teacher correcting a student's answ -
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Law of Effect
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When satisfaction follows association, it is more likely to be repeated. -
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Agent-Environment Framework
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In machines, reinforcement learning (RL) is implemented using an agent-environment framework. The agent interacts with an environment by taking actions based on -
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Q-learning
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Q-learning is a model-free reinforcement learning algorithm that enables an agent to learn an optimal policy for decision-making. It works by estimating the Q-v -
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Deep reinforcement learning
DRL is a type of machine learning where an agent learns to make decisions by trial and error, guided by rewards or penalties, using deep neural networks. Unlike -
is_parent Repetitio ·
Experiential learning, Unsupervised learning, Supervised learning, Classifiers & Machine Learning ... -
is_parent Hebb's Law
"Cells that fire together, wire together." -
is_parent Conditioning ·
Conditioning is a learning process where an individual forms associations between stimuli or behaviors and their outcomes. It can be divided into two main types
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is_parent Social learning
Social learning is "a process in which individuals learn by observing the behaviors of others, imitating them, and experiencing the consequences of these action-
is_parent Social Learning Theory
Albert Bandura’s Social Learning Theory (1977) revolutionized psychology by emphasizing that learning occurs in a social context through observation, imitation,
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is_parent Machine Learning ·
Machine Learning -
is_parent Peer learning ·
Peer learning -
is_parent Human-Machine Peer Learning ·
Human-Machine Peer Learning -
is_parent Teaching, Pedagogy, Didactics ·
Teaching, Pedagogy, Didactics -
is_parent Artificial Teacher Avatars ·
Artificial Teacher Avatars -
is_parent Extended Educational Environments ·
Extended Educational Environments -
is_parent Four pillars of learning
Active engagement:::Attention:::Error Feedback:::Consolidation-
is_parent Active engagement ·
Active engagement -
is_parent Attention ·
Attention -
is_parent Error Feedback ·
Error Feedback -
is_parent Consolidation ·
Consolidation
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