Generalization (learning)

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Generalization is the concept that humans, other animals, and artificial neural networks use past learning in present situations of learning if the conditions in the situations are regarded as similar. [1] The learner uses generalized patterns, principles, and other similarities between past experiences and novel experiences to more efficiently navigate the world. [2] For example, if a person has learned in the past that every time they eat an apple, their throat becomes itchy and swollen, they might assume they are allergic to all fruit. When this person is offered a banana to eat, they reject it upon assuming they are also allergic to it through generalizing that all fruits cause the same reaction. Although this generalization about being allergic to all fruit based on experiences with one fruit could be correct in some cases, it may not be correct in all. Both positive and negative effects have been shown in education through learned generalization and its contrasting notion of discrimination learning.

Contents

Overview

Generalization is understood to be directly tied to the transfer of knowledge across multiple situations. [3] The knowledge to be transferred is often referred to as abstractions, because the learner abstracts a rule or pattern of characteristics from previous experiences with similar stimuli. [2] Generalization allows humans and animals to recognize the similarities in knowledge acquired in one circumstance, allowing for transfer of knowledge onto new situations. This idea rivals the theory of situated cognition, instead stating that one can apply past knowledge to learning in new situations and environments.

Generalization can be supported and partly explained by the connectionism approach. [4] Just as artificial intelligences learn to distinguish between different categories by applying past learning to novel situations, humans and animals generalize previously learned properties and patterns onto new situations, thus connecting the novel experience to past experiences that are similar in one or more ways. This creates a pattern of connections that allows the learner to classify and make assumptions about the novel stimulus, such as when previous experience with seeing a canary allows the learner to predict what other birds will be like. This categorization is a foundational aspect of generalizing.

Research on generalization

In scientific studies looking at generalization, a generalization gradient is often used. This tool is used to measure how often and how much animals or humans respond to certain stimuli, depending on whether the stimuli are perceived to be similar or different. The curvilinear shape of the gradient is achieved by placing the perceived similarity of a stimulus on the x-axis and the strength of the response on the y-axis. [5] For example, when measuring responses to color, it is expected that subjects will respond to colors that are similar to each other, like shades of pink after being exposed to red, as opposed to a non-similar shade of blue. [6] The gradient is relatively predictable, with the response to similar stimuli being slightly less strong than the response to the conditioned stimulus, then steadily declining as the presented stimuli become increasingly dissimilar. [7]

Several studies have suggested that generalization is a fundamental and naturally-occurring learning process for humans. Nine-month-old infants require very few (sometimes only 3) experiences with a category before learning to generalize. [2] In fact, infants generalize so well during early stages of development (such as learning to recognize specific sounds as language) that it can be hard for them to discriminate between variations of the generalized stimuli at later stages of development (such as failing to distinguish between the subtly different sounds of similar phonemes). [2] One potential explanation for why children are such efficient learners is that they operate in accordance with the goal of making their world more predictable, therefore encouraging them to hold strongly to generalizations that effectively help them to navigate their environment. [2]

Some evidence suggests that children are born with innate processes for accurately generalizing things. For example, children tend to generalize based on taxonomic rather than thematic similarities (an experience with one ball leads to the child identifying other ball-shaped objects as “ball” rather than labeling a bat as “ball” because a bat is used to hit a ball). [2]

Wakefield, Hall, James, and Goldin (2018) found that children are more flexible in generalizing new verbs when they are taught the verb by observing gestures as opposed to being taught by performing the action themselves. [8] When helping a child learn a new word, providing more examples of the word increases the child's capacity to generalize the word to different contexts and situations. Furthermore, writing interventions for grade-school students yield better results when the intervention actively targets generalization as an outcome. [9]

Generalization has been shown to be refined and/or stabilized after sleep. [10]

Implications

Without the ability to generalize, it would likely be very difficult to navigate the world in a useful way. [2] For example, generalization is an important part of how humans learn to trust unfamiliar people [11] and a necessary element in language acquisition. [12]

For a person who lacked the capacity to generalize from one experience to the next, every instance of a dog would be completely separated from other instances of dogs, so prior experience would do nothing to help the person know how to interact with this seemingly new stimulus. [2] In fact, even if the person experienced the very same dog multiple times, he or she would have no way of knowing what to expect and each instance would be as if the individual were encountering a dog for the first time. Therefore, generalization is a valuable and integral part of learning and everyday life.

Generalization is shown to have implications on the use of the spacing effect in educational settings. [13] In the past, it was thought that the information forgotten between periods of learning when implementing spaced presentation inhibited generalization. In more recent years, this forgetting has been seen as promoting generalization through repetition of information during each occasion of spaced learning. The effects of gaining long-term generalization knowledge through spaced learning can be compared with that of massed learning (lengthy and all at once; for example, cramming the night before an exam) [14] in which a person only gains short-term knowledge, decreasing the likelihood of establishing generalization.

Generalization is also considered to be an important factor in procedural memory, such as the near-automatic memory processes necessary for driving a car. [2] Without being able to generalize from previous experiences driving, a person would essentially need to relearn how to drive every time he or she encountered a new street.

Not all of generalization's effects are beneficial, however. An important part of learning is knowing when not to generalize, which is called discrimination learning. Were it not for discrimination learning, humans and animals would struggle to respond correctly to different situations. [15] For example, a dog may be trained to come to its owner when it hears a whistle. If the dog generalizes this training, it may not discriminate between the sound of the whistle and other stimuli, so it would come running to its owner when it hears any high-pitched noise.

Fear generalization

A specific type of generalization, fear generalization, occurs when a person associates fears learned in the past through classical conditioning to similar situations, events, people, and objects in their present. This is important for the survival of the organism; humans and animals need to be able to assess aversive situations and respond appropriately based on generalizations made from past experiences. [16]

When fear generalization becomes maladaptive it is connected to many anxiety disorders. [17] This maladaptation is often referred to as the overgeneralization of fear and can also lead to the development of posttraumatic stress disorder. [18] Overgeneralization is hypothetically attributed to “dysregulation of prefrontal-amygdalo-hippocampal circuitry” (Banich, et al., 2010, p. 21). [2]

One of the earliest studies about fear generalization in humans was conducted by Watson and Raynor (1920): the Little Albert experiment. In their study, an infant known as Little Albert was exposed to various kinds of animals, none of which elicited a fear response from Little Albert. However, after 7 pairings of a white rat and the sound of a hammer clanging against a steel bar (which did elicit a fear response), the 11-month old child began to cry and try to get away from the white rat even without the loud noise. Months later, additional trials showed that Little Albert had generalized his fear response to things that were similar to the white rat, including a dog, a rabbit, and a fur coat. [2]

Brain regions involved in fear generalization include the amygdala and the hippocampus. [2] The hippocampus seems to be more involved in the development of context fear generalization (developing a generalized fear for a specific environment) than stimulus fear generalization (such as Little Albert's acquisition of a fear response to white, furry objects). The amygdala, which is associated with all types of emotional responses, is fundamental in developing a classically conditioned fear response to either a stimulus or the context in which it is found. [2]

Generalization in machine learning

This section is an excerpt from Machine learning § Generalization.[ edit ]
The difference between optimization and machine learning arises from the goal of generalization: while optimization algorithms can minimize the loss on a training set, machine learning is concerned with minimizing the loss on unseen samples. Characterizing the generalization of various learning algorithms is an active topic of current research, especially for deep learning algorithms.

See also

Related Research Articles

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<span class="mw-page-title-main">Phobia</span> Anxiety disorder classified by a persistent and excessive fear of an object or situation

A phobia is an anxiety disorder, defined by a persistent and excessive fear of an object or situation. Phobias typically result in a rapid onset of fear and are usually present for more than six months. Those affected go to great lengths to avoid the situation or object, to a degree greater than the actual danger posed. If the object or situation cannot be avoided, they experience significant distress. Other symptoms can include fainting, which may occur in blood or injury phobia, and panic attacks, often found in agoraphobia and emetophobia. Around 75% of those with phobias have multiple phobias.

Operant conditioning, also called instrumental conditioning, is a learning process where behaviors are modified through the association of stimuli with reinforcement or punishment. In it, operants—behaviors that affect one's environment—are conditioned to occur or not occur depending on the environmental consequences of the behavior.

<span class="mw-page-title-main">Learning</span> Process of acquiring new knowledge

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In reinforcement theory, it is argued that human behavior is a result of "contingent consequences" to human actions. The publication pushes forward the idea that "you get what you reinforce". This means that behavior, when given the right types of reinforcers, can be changed for the better and negative behavior can be reinforced away.

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Habituation is a form of non-associative learning in which an innate (non-reinforced) response to a stimulus decreases after repeated or prolonged presentations of that stimulus. Responses that habituate include those that involve the intact organism or those that involve only components of the organism. The broad ubiquity of habituation across all biologic phyla has resulted in it being called "the simplest, most universal form of learning...as fundamental a characteristic of life as DNA." Functionally-speaking, by diminishing the response to an inconsequential stimulus, habituation is thought to free-up cognitive resources to other stimuli that are associated with biologically important events. For example, organisms may habituate to repeated sudden loud noises when they learn these have no consequences. A progressive decline of a behavior in a habituation procedure may also reflect nonspecific effects such as fatigue, which must be ruled out when the interest is in habituation. Habituation is clinically relevant, as a number of neuropsychiatric conditions, including autism, schizophrenia, migraine, and Tourette's, show reductions in habituation to a variety of stimulus-types both simple (tone) and complex (faces).

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In behavioral psychology, the assumption of generality is the assumption that the results of experiments involving schedules of reinforcement, conducted on non-human subjects, can be generalized to apply to humans. If the assumption holds, many aspects of daily human life can be understood in terms of these results. The naturalization of sunlight helps our bodies to stay awake and keep motivated. The darkness that comes with night tells our body to slow down for the day and get some rest. The ability to survive comes with generality. Experiments have been done to test inescapability and insolubility.

Shaping is a conditioning paradigm used primarily in the experimental analysis of behavior. The method used is differential reinforcement of successive approximations. It was introduced by B. F. Skinner with pigeons and extended to dogs, dolphins, humans and other species. In shaping, the form of an existing response is gradually changed across successive trials towards a desired target behavior by reinforcing exact segments of behavior. Skinner's explanation of shaping was this:

We first give the bird food when it turns slightly in the direction of the spot from any part of the cage. This increases the frequency of such behavior. We then withhold reinforcement until a slight movement is made toward the spot. This again alters the general distribution of behavior without producing a new unit. We continue by reinforcing positions successively closer to the spot, then by reinforcing only when the head is moved slightly forward, and finally only when the beak actually makes contact with the spot. ... The original probability of the response in its final form is very low; in some cases it may even be zero. In this way we can build complicated operants which would never appear in the repertoire of the organism otherwise. By reinforcing a series of successive approximations, we bring a rare response to a very high probability in a short time. ... The total act of turning toward the spot from any point in the box, walking toward it, raising the head, and striking the spot may seem to be a functionally coherent unit of behavior; but it is constructed by a continual process of differential reinforcement from undifferentiated behavior, just as the sculptor shapes his figure from a lump of clay.

Concept learning, also known as category learning, concept attainment, and concept formation, is defined by Bruner, Goodnow, & Austin (1967) as "the search for and listing of attributes that can be used to distinguish exemplars from non exemplars of various categories". More simply put, concepts are the mental categories that help us classify objects, events, or ideas, building on the understanding that each object, event, or idea has a set of common relevant features. Thus, concept learning is a strategy which requires a learner to compare and contrast groups or categories that contain concept-relevant features with groups or categories that do not contain concept-relevant features.

In behavioral psychology, stimulus control is a phenomenon in operant conditioning that occurs when an organism behaves in one way in the presence of a given stimulus and another way in its absence. A stimulus that modifies behavior in this manner is either a discriminative stimulus or stimulus delta. For example, the presence of a stop sign at a traffic intersection alerts the driver to stop driving and increases the probability that braking behavior occurs. Stimulus control does not force behavior to occur, as it is a direct result of historical reinforcement contingencies, as opposed to reflexive behavior elicited through classical conditioning.

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Discrimination learning is defined in psychology as the ability to respond differently to different stimuli. This type of learning is used in studies regarding operant and classical conditioning. Operant conditioning involves the modification of a behavior by means of reinforcement or punishment. In this way, a discriminative stimulus will act as an indicator to when a behavior will persist and when it will not. Classical conditioning involves learning through association when two stimuli are paired together repeatedly. This conditioning demonstrates discrimination through specific micro-instances of reinforcement and non-reinforcement. This phenomenon is considered to be more advanced than learning styles such as generalization and yet simultaneously acts as a basic unit to learning as a whole. The complex and fundamental nature of discrimination learning allows for psychologists and researchers to perform more in-depth research that supports psychological advancements. Research on the basic principles underlying this learning style has their roots in neuropsychology sub-processes.

Psychological behaviorism is a form of behaviorism — a major theory within psychology which holds that generally human behaviors are learned — proposed by Arthur W. Staats. The theory is constructed to advance from basic animal learning principles to deal with all types of human behavior, including personality, culture, and human evolution. Behaviorism was first developed by John B. Watson (1912), who coined the term "behaviorism," and then B. F. Skinner who developed what is known as "radical behaviorism." Watson and Skinner rejected the idea that psychological data could be obtained through introspection or by an attempt to describe consciousness; all psychological data, in their view, was to be derived from the observation of outward behavior. The strategy of these behaviorists was that the animal learning principles should then be used to explain human behavior. Thus, their behaviorisms were based upon research with animals.

<span class="mw-page-title-main">Universal law of generalization</span> Theory of cognition

The universal law of generalization is a theory of cognition stating that the probability of a response to one stimulus being generalized to another is a function of the “distance” between the two stimuli in a psychological space. It was introduced in 1987 by Roger N. Shepard, who began researching mechanisms of generalization while he was still a graduate student at Yale:

"I was now convinced that the problem of generalization was the most fundamental problem confronting learning theory. Because we never encounter exactly the same total situation twice, no theory of learning can be complete without a law governing how what is learned in one situation generalizes to another"


Human contingency learning (HCL) is the observation that people tend to acquire knowledge based on whichever outcome has the highest probability of occurring from particular stimuli. In other words, individuals gather associations between a certain behaviour and a specific consequence. It is a form of learning for many organisms.

Association in psychology refers to a mental connection between concepts, events, or mental states that usually stems from specific experiences. Associations are seen throughout several schools of thought in psychology including behaviorism, associationism, psychoanalysis, social psychology, and structuralism. The idea stems from Plato and Aristotle, especially with regard to the succession of memories, and it was carried on by philosophers such as John Locke, David Hume, David Hartley, and James Mill. It finds its place in modern psychology in such areas as memory, learning, and the study of neural pathways.

References

  1. ↑ Gluck, Mark A.; Mercado, Eduardo; Myers, Catherine E. (2011). Learning and memory : from brain to behavior (2nd ed.). New York: Worth Publishers. p. 209. ISBN   9781429240147.
  2. 1 2 3 4 5 6 7 8 9 10 11 12 13 Banich, M. T., Dukes, P., & Caccamise, D. (2010). Generalization of knowledge: Multidisciplinary perspectives. Psychology Press.
  3. ↑ Walker, J. E.; Shea, T. M.; Bauer, A.M. "Generalization and the Effects of Consequences | Education.com". www.education.com. Retrieved 5 May 2016.
  4. ↑ Goldstein, B. E. (2015). Cognitive psychology: connecting mind research and everyday experience. W. Ross MacDonald School Resource Services Library.
  5. ↑ Boddez, Y., Bennett, M. P., van Esch, S., & Beckers, T. (2017). Bending rules: the shape of the perceptual generalisation gradient is sensitive to inference rules. Cognition & Emotion, 31(7), 1444–1452. https://doi.org/10.1080/02699931.2016.1230541
  6. ↑ Gluck, Mark A.; Mercado, Eduardo; Myers, Catherine E. (2014). Learning and memory : from brain to behavior (2nd ed.). New York: Worth Publishers. p. 212. ISBN   9781429240147.
  7. ↑ The Editors of Encyclopaedia Britannica. (2019, September 30). Generalization. Retrieved from https://www.britannica.com/topic/generalization
  8. ↑ Wakefield, E. M., Hall, C., James, K. H., & Goldin, M. S. (2018). Gesture for generalization: gesture facilitates flexible learning of words for actions on objects. Developmental Science, 21(5), 1. https://doi.org/10.1111/desc.12656
  9. ↑ Hier, B. O., Eckert, T. L., Viney, E. A., & Meisinger, E. (2019). Generalization and maintenance effects of writing fluency intervention strategies for elementary-age students: A randomized controlled trial. School Psychology Review, 48(4), 377. https://doi.org/10.17105/SPR-2017-0123.V48-4
  10. ↑ Fenn, KM; Nusbaum, HC; Margoliash, D (2003). "Consolidation during sleep of perceptual learning of spoken language". Nature. 425 (6958): 614–6. doi:10.1038/nature01951. PMID   14534586. S2CID   904751.
  11. ↑ FeldmanHall, O., Dunsmoor, J. E., Tompary, A., Hunter, L. E., Todorov, A., & Phelps, E. A. (2018). Stimulus generalization as a mechanism for learning to trust. Proceedings of the National Academy of Sciences, 115(7). doi : 10.1073/pnas.1715227115
  12. ↑ Arnon, I.; Clark, E. V., eds. (2011). Experience, variation and generalization: Learning a first language. doi:10.1111/j.1540-4781.2012.01368.x. ISBN   978-9027234773. S2CID   60234960.
  13. ↑ Vlach, Haley A. (September 2014). "The Spacing Effect in Children's Generalization of Knowledge: Allowing Children Time to Forget Promotes Their Ability to Learn". Child Development Perspectives. 8 (3): 163–168. doi: 10.1111/cdep.12079 .
  14. ↑ Gluck, Mark A.; Mercado, Eduardo; Myers, Catherine E. (2014). Learning and memory : from brain to behavior (2nd ed.). New York: Worth Publishers. p. 312. ISBN   9781429240147.
  15. ↑ Cherry, K. (2019, November 26). How stimulus generalization influences learning. Retrieved from https://www.verywellmind.com/what-is-stimulus-generalization-2795885
  16. ↑ Asok, A., Kandel, E. R., & Rayman, J. B. (2019). The neurobiology of fear generalization. Frontiers in Behavioral Neuroscience, 12. doi: 10.3389/fnbeh.2018.00329
  17. ↑ Dymond, Simon; Dunsmoor, Joseph E.; Vervliet, Bram; Roche, Bryan; Hermans, Dirk (September 2015). "Fear Generalization in Humans: Systematic Review and Implications for Anxiety Disorder Research" (PDF). Behavior Therapy. 46 (5): 561–582. doi:10.1016/j.beth.2014.10.001. PMID   26459838.
  18. ↑ Besnard, Antoine; Sahay, Amar (12 June 2015). "Adult Hippocampal Neurogenesis, Fear Generalization, and Stress". Neuropsychopharmacology. 41 (1): 24–44. doi:10.1038/npp.2015.167. PMC   4677119 . PMID   26068726.
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