Chapter 6 Learning
... Jacques Loeb argued that all animal behavior, and most human behavior, could be explained with stimulusresponse psychology. Stimulus-response psychology attempts to explain behavior in terms of how each stimulus triggers a response. Flinching away from a blow and shading one’s eyes from a stro ...
... Jacques Loeb argued that all animal behavior, and most human behavior, could be explained with stimulusresponse psychology. Stimulus-response psychology attempts to explain behavior in terms of how each stimulus triggers a response. Flinching away from a blow and shading one’s eyes from a stro ...
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... which stems not from an understanding of connections, but from an ignorance of boundaries. Creative thinking in higher education can only be expressed productively within a particular domain. The student must have a strong foundation in the strategies and skills of the domain in order to make connec ...
... which stems not from an understanding of connections, but from an ignorance of boundaries. Creative thinking in higher education can only be expressed productively within a particular domain. The student must have a strong foundation in the strategies and skills of the domain in order to make connec ...
Posterior cingulate cortex: adapting behavior to a
... Recent studies have provided evidence that both humans and nonhuman animals often employ sophisticated, model-based assumptions when learning about their environments [7,11,15]. That is, agents first determine an appropriate set of constructs by which to model the world, and then update the paramete ...
... Recent studies have provided evidence that both humans and nonhuman animals often employ sophisticated, model-based assumptions when learning about their environments [7,11,15]. That is, agents first determine an appropriate set of constructs by which to model the world, and then update the paramete ...
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... an open length of time period. IHDR overcomes both problems by allowing dynamic spawning nodes from a growing tree, while shallow nodes and unmatched leaf nodes serving as the long term memory. However, IHDR is not an in-place learner (e.g., computing covariance matrix for each neuron). The multi-la ...
... an open length of time period. IHDR overcomes both problems by allowing dynamic spawning nodes from a growing tree, while shallow nodes and unmatched leaf nodes serving as the long term memory. However, IHDR is not an in-place learner (e.g., computing covariance matrix for each neuron). The multi-la ...
Associationism
... referred to as an ‘unconditioned response’ (UR). In Pavlov’s canonical experiment, the US was a meat powder, as the smell of meat automatically brought about salivation (UR) in his canine subjects. The US is then paired with a neutral stimulus, such as a bell. Over time, the contiguity between the U ...
... referred to as an ‘unconditioned response’ (UR). In Pavlov’s canonical experiment, the US was a meat powder, as the smell of meat automatically brought about salivation (UR) in his canine subjects. The US is then paired with a neutral stimulus, such as a bell. Over time, the contiguity between the U ...
Reinforcement Learning Using a Continuous Time Actor
... residual gradient (Eq. 7) to Eq. 10. As noted by Doya [19], the form of the learning rule in Eq. 10 is a continuous version of the discrete TD(l) [1,27] with function approximation (here with l~0). This has been shown to converge with probability 1 [28,29], even in the case of infinite (but countabl ...
... residual gradient (Eq. 7) to Eq. 10. As noted by Doya [19], the form of the learning rule in Eq. 10 is a continuous version of the discrete TD(l) [1,27] with function approximation (here with l~0). This has been shown to converge with probability 1 [28,29], even in the case of infinite (but countabl ...
Intelligent Information Retrieval and Web Search
... – Entity relations from the original WebKB domain (Craven et al. 1998) – Predicates include Faculty, Student, Project, CourseTA, etc. ...
... – Entity relations from the original WebKB domain (Craven et al. 1998) – Predicates include Faculty, Student, Project, CourseTA, etc. ...
A Neurocomputational Instructional Indicator of Working Memory
... number of topics increases the cardinality of the environment space becomes explosively large1. The learner needs to explore that space in the most beneficial way, having to select the best completion path (i.e. traversing the environment, from topic to topic, in such an ordering so that a high degr ...
... number of topics increases the cardinality of the environment space becomes explosively large1. The learner needs to explore that space in the most beneficial way, having to select the best completion path (i.e. traversing the environment, from topic to topic, in such an ordering so that a high degr ...
Ohio Professional Development Standards
... knowledge and skills; attitudes and beliefs; and motivation and behavior necessary to create high levels of learning for all students. Professional development informs educators about research and ensures that they have the knowledge, skills and dispositions to access and use research in their pract ...
... knowledge and skills; attitudes and beliefs; and motivation and behavior necessary to create high levels of learning for all students. Professional development informs educators about research and ensures that they have the knowledge, skills and dispositions to access and use research in their pract ...
Learning to represent reward structure: A key to adapting to complex
... performed well, V (ei ) = ri + V (ei+1 ) should hold on average, and it is thus not well established if both ends of the equation differ. Therefore, it uses the difference as a learning signal or TD error, ı(ei ) = ri + V (ei+1 ) − V (ei ), as the name indicates (i.e., the temporal difference of v ...
... performed well, V (ei ) = ri + V (ei+1 ) should hold on average, and it is thus not well established if both ends of the equation differ. Therefore, it uses the difference as a learning signal or TD error, ı(ei ) = ri + V (ei+1 ) − V (ei ), as the name indicates (i.e., the temporal difference of v ...
Deep Belief Networks Learn Context Dependent Behavior Florian Raudies *
... [8,9,10,11]. Models of prefrontal cortex have attempted to simulate how neural circuits could provide the rules for action selection during behavioral tasks based on the context of the decision in addition to specific sensory input cues [12,13,14]. However, many previous models of prefrontal cortex ...
... [8,9,10,11]. Models of prefrontal cortex have attempted to simulate how neural circuits could provide the rules for action selection during behavioral tasks based on the context of the decision in addition to specific sensory input cues [12,13,14]. However, many previous models of prefrontal cortex ...
Social learning spaces - Wenger
... projects and the countries involved. Communities of practice, when they work well, are quintessential examples of social learning spaces. The learning space of a community is built through a history of learning together over time. Commitment derives from identification with a shared domain of intere ...
... projects and the countries involved. Communities of practice, when they work well, are quintessential examples of social learning spaces. The learning space of a community is built through a history of learning together over time. Commitment derives from identification with a shared domain of intere ...
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... incremental principle component analysis and showed that the neural coding can reconstruct the original signal to a large degree. Miikkulainen et al. 2005 [23] have developed a multilayer network with nearby excitory interactions surrounded by inhibitory interactions. There have been many other stud ...
... incremental principle component analysis and showed that the neural coding can reconstruct the original signal to a large degree. Miikkulainen et al. 2005 [23] have developed a multilayer network with nearby excitory interactions surrounded by inhibitory interactions. There have been many other stud ...
Behavioral and Neural Properties of Social Reinforcement Learning
... Daw, 2011). The learned association generates a neural signal to the cue that previously was associated with the reward itself (Schultz et al., 1997; O’Doherty et al., 2006). The current study examines whether similar changes in behavior (response latencies) and neural circuitry engaged during basic ...
... Daw, 2011). The learned association generates a neural signal to the cue that previously was associated with the reward itself (Schultz et al., 1997; O’Doherty et al., 2006). The current study examines whether similar changes in behavior (response latencies) and neural circuitry engaged during basic ...
unit 6 study guide
... a. the taste of food. b. salivation to the taste of food. c. the sound of a tone. d. salivation to the sound of a tone. e. the anticipation of food. 23. In classical conditioning, the ________ signals the impending occurrence of the ________. a. US; CS b. UR; CR c. CS; US d. CR; UR e. US; CR 24. Whi ...
... a. the taste of food. b. salivation to the taste of food. c. the sound of a tone. d. salivation to the sound of a tone. e. the anticipation of food. 23. In classical conditioning, the ________ signals the impending occurrence of the ________. a. US; CS b. UR; CR c. CS; US d. CR; UR e. US; CR 24. Whi ...
Goal-direction and top-down control
... the day, and so the animal was forced to learn the category of stimuli in order to make the appropriate response to novel exemplars (i.e. those they had never before seen). Neurons in PFC and BG played different roles during these two types of behaviours. Early on, when they could acquire specific s ...
... the day, and so the animal was forced to learn the category of stimuli in order to make the appropriate response to novel exemplars (i.e. those they had never before seen). Neurons in PFC and BG played different roles during these two types of behaviours. Early on, when they could acquire specific s ...
Modelling fast stimulus-response association learning along the
... There appear to be at least two stages in learning SR rules, the first being driven by the instruction and the second driven by actual or possibly mentally simulated practice. The first uses a network of PFC, PM and PPC areas (Ruge and Wolfensteller, 2009; Cole et al, 2010; Brass et al., 2009). The ...
... There appear to be at least two stages in learning SR rules, the first being driven by the instruction and the second driven by actual or possibly mentally simulated practice. The first uses a network of PFC, PM and PPC areas (Ruge and Wolfensteller, 2009; Cole et al, 2010; Brass et al., 2009). The ...
Classical conditioning - Exp In Social Studies
... How Do We Learn? • Associative learning – learning that certain events occur together. The events may be two stimuli (as in classical conditioning) or a response and its consequence (as in operant conditioning). ...
... How Do We Learn? • Associative learning – learning that certain events occur together. The events may be two stimuli (as in classical conditioning) or a response and its consequence (as in operant conditioning). ...
Neurons with Two Sites of Synaptic Integration Learn Invariant
... Neurons in mammalian cerebral cortex combine specic responses with respect to some stimulus features with invariant responses to other stimulus features. For example, in primary visual cortex, complex cells code for orientation of a contour but ignore its position to a certain degree. In higher are ...
... Neurons in mammalian cerebral cortex combine specic responses with respect to some stimulus features with invariant responses to other stimulus features. For example, in primary visual cortex, complex cells code for orientation of a contour but ignore its position to a certain degree. In higher are ...
review - NYU Psychology
... understood without recognizing the role of other regions in the same fear learning circuit, this kind of learning cannot be completely understood without considering the intricacy of the natural environment in which it occurs. For example, fear conditioning procedures have traditionally examined lea ...
... understood without recognizing the role of other regions in the same fear learning circuit, this kind of learning cannot be completely understood without considering the intricacy of the natural environment in which it occurs. For example, fear conditioning procedures have traditionally examined lea ...
Spontaneous Imitation in Animals and Humans
... instinctive actions to a more generalized set of responses, depending on the species. In addition, imitation may occur only when the model is present, or it may be delayed for some time after the model has been removed. Such delayed imitation is often regarded as a more complex form, since it involv ...
... instinctive actions to a more generalized set of responses, depending on the species. In addition, imitation may occur only when the model is present, or it may be delayed for some time after the model has been removed. Such delayed imitation is often regarded as a more complex form, since it involv ...
Kelleher,M. and Poell,R. FACING UP TO THE LEARNING
... normative or prescriptive business-school management concept that is founded on hard-nosed American/Anglo-Saxon economic principles of organisational effectiveness. They criticise the use of sophisticated cultural and psychological theories by modern management to maximise benefits for the company ...
... normative or prescriptive business-school management concept that is founded on hard-nosed American/Anglo-Saxon economic principles of organisational effectiveness. They criticise the use of sophisticated cultural and psychological theories by modern management to maximise benefits for the company ...
Hebbian Learning of Bayes Optimal Decisions
... Evolution is likely to favor those biological organisms which are able to maximize the chance of achieving correct decisions in response to multiple unreliable sources of evidence. Hence one may argue that probabilistic inference, rather than logical inference, is the ”mathematics of the mind”, and ...
... Evolution is likely to favor those biological organisms which are able to maximize the chance of achieving correct decisions in response to multiple unreliable sources of evidence. Hence one may argue that probabilistic inference, rather than logical inference, is the ”mathematics of the mind”, and ...
Continuous transformation learning of translation
... network with a single layer of forward synaptic connections between an input layer of neurons and an output layer. Initially the forward synaptic weights are set to random values. The top part a shows the initial presentation of a stimulus to the network in position 1. Activation from the (shaded) a ...
... network with a single layer of forward synaptic connections between an input layer of neurons and an output layer. Initially the forward synaptic weights are set to random values. The top part a shows the initial presentation of a stimulus to the network in position 1. Activation from the (shaded) a ...