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Bayesian Cognitive Science
Bayesian cognitive science, also known as computational cognitive science, is an approach to cognitive science concerned with the rational analysis of cognition through the use of Bayesian inference and cognitive modeling. The term "computational" refers to the computational level of analysis as put forth by David Marr. This work often consists of testing the hypothesis that cognitive systems behave like rational Bayesian agents in particular types of tasks. Past work has applied this idea to categorization, language, motor control, sequence learning, reinforcement learning and theory of mind. At other times, Bayesian rationality is ''assumed'', and the goal is to infer the knowledge that agents have, and the mental representations that they use. It is important to contrast this with the ordinary use of Bayesian inference in cognitive science, which is independent of rational modeling (see e.gMichael Lee's work. See also * Active inference * Bayesian approaches to brai ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Rational Analysis
Rational analysis is a theoretical framework, methodology, and research program in cognitive science that has been developed by John Anderson.Anderson, J. R. (1990). "The adaptive character of thought". Hillsdale, NJ: Lawrence Erlbaum Associates. The goal of rational analysis as a research program is to explain the function and purpose of cognitive processes and to discover the structure of the mind. Chater and Oaksford contrast it with the mechanistic explanations of cognition offered by both computational models and neuroscience. Rational analysis starts from the assumption that the mind is adapted to its environment. Rational analysis uses this assumption to investigate the structure and purpose of representations and cognitive processes by studying the structure of the environment. The methodology of rational analysis comprises six steps: #Goals: Specify precisely the goals of the cognitive system. #Environment: Develop a formal model of the environment to which the system is ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bayesian Inference
Bayesian inference is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. Bayesian inference is an important technique in statistics, and especially in mathematical statistics. Bayesian updating is particularly important in the dynamic analysis of a sequence of data. Bayesian inference has found application in a wide range of activities, including science, engineering, philosophy, medicine, sport, and law. In the philosophy of decision theory, Bayesian inference is closely related to subjective probability, often called "Bayesian probability". Introduction to Bayes' rule Formal explanation Bayesian inference derives the posterior probability as a consequence of two antecedents: a prior probability and a "likelihood function" derived from a statistical model for the observed data. Bayesian inference computes the posterior probability according to Bayes' theorem: ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cognitive Model
A cognitive model is an approximation of one or more cognitive processes in humans or other animals for the purposes of comprehension and prediction. There are many types of cognitive models, and they can range from box-and-arrow diagrams to a set of equations to software programs that interact with the same tools that humans use to complete tasks (e.g., computer mouse and keyboard). Relationship to cognitive architectures Cognitive models can be developed within or without a cognitive architecture, though the two are not always easily distinguishable. In contrast to cognitive architectures, cognitive models tend to be focused on a single cognitive phenomenon or process (e.g., list learning), how two or more processes interact (e.g., visual search bsc1780 decision making), or making behavioral predictions for a specific task or tool (e.g., how instituting a new software package will affect productivity). Cognitive architectures tend to be focused on the structural properties of the m ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
David Marr (neuroscientist)
David Courtenay Marr (19 January 1945 – 17 November 1980) from the ''International Encyclopaedia of Social and Behavioral Sciences'', by Shimon Edelman and Lucia M. Vaina; published 2001-01-08; archived at ; retrieved 2021-07-21 was a British and physiologist. Marr integrated results from , |
Categorization
Categorization is the ability and activity of recognizing shared features or similarities between the elements of the experience of the world (such as Object (philosophy), objects, events, or ideas), organizing and classifying experience by associating them to a more abstract group (that is, a category, class, or type), on the basis of their traits, features, similarities or other criteria that are Universal (metaphysics), universal to the group. Categorization is considered one of the most fundamental cognitive abilities, and as such it is studied particularly by psychology and cognitive linguistics. Categorization is sometimes considered synonymous with classification (cf., Classification (general theory)#Synonyms and near-synonyms, Classification synonyms). Categorization and classification allow humans to organize things, objects, and ideas that exist around them and simplify their understanding of the world. Categorization is something that humans and other organisms ''do ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Motor Control
Motor control is the regulation of movement in organisms that possess a nervous system. Motor control includes reflexes as well as directed movement. To control movement, the nervous system must integrate multimodal sensory information (both from the external world as well as proprioception) and elicit the necessary signals to recruit muscles to carry out a goal. This pathway spans many disciplines, including multisensory integration, signal processing, coordination, biomechanics, and cognition, and the computational challenges are often discussed under the term sensorimotor control. Successful motor control is crucial to interacting with the world to carry out goals as well as for posture, balance, and stability. Some researchers (mostly neuroscientists studying movement, such as Daniel Wolpert and Randy Flanagan) argue that motor control is the reason brains exist at all. Neural control of muscle force All movements, e.g. touching your nose, require motor neurons to fire ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sequence Learning
In cognitive psychology, sequence learning is inherent to human ability because it is an integrated part of conscious and nonconscious learning as well as activities. Sequences of information or sequences of actions are used in various everyday tasks: "from sequencing sounds in speech, to sequencing movements in typing or playing instruments, to sequencing actions in driving an automobile." Sequence learning can be used to study skill acquisition and in studies of various groups ranging from neuropsychological patients to infants. According to Ritter and Nerb, “The order in which material is presented can strongly influence what is learned, how fast performance increases, and sometimes even whether the material is learned at all.” Sequence learning, more known and understood as a form of explicit learning, is now also being studied as a form of implicit learning as well as other forms of learning. Sequence learning can also be referred to as sequential behavior, behavior sequenci ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Reinforcement Learning
Reinforcement learning (RL) is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Reinforcement learning differs from supervised learning in not needing labelled input/output pairs to be presented, and in not needing sub-optimal actions to be explicitly corrected. Instead the focus is on finding a balance between exploration (of uncharted territory) and exploitation (of current knowledge). The environment is typically stated in the form of a Markov decision process (MDP), because many reinforcement learning algorithms for this context use dynamic programming techniques. The main difference between the classical dynamic programming methods and reinforcement learning algorithms is that the latter do not assume knowledge of an exact mathematica ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Theory Of Mind
In psychology, theory of mind refers to the capacity to understand other people by ascribing mental states to them (that is, surmising what is happening in their mind). This includes the knowledge that others' mental states may be different from one's own states and include beliefs, desires, intentions, emotions, and thoughts. Possessing a functional theory of mind is considered crucial for success in everyday human social interactions. People use such a theory when analyzing, judging, and inferring others' behaviors. The discovery and development of theory of mind primarily came from studies done with animals and infants. Factors including drug and alcohol consumption, language development, cognitive delays, age, and culture can affect a person's capacity to display theory of mind. It has been proposed that deficits in theory of mind can occur in people with autism (although this is contentious), anorexia nervosa, schizophrenia, dysphoria, attention deficit hyperactivity diso ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Active Inference
The free energy principle is a mathematical principle in biophysics and cognitive science that provides a formal account of the representational capacities of physical systems: that is, why things that exist look as if they track properties of the systems to which they are coupled. It establishes that the dynamics of physical systems minimise a quantity known as surprisal (which is just the negative log probability of some outcome); or equivalently, its variational upper bound, called free energy. The principle is formally related to variational Bayesian methods and was originally introduced by Karl Friston as an explanation for embodied perception-action loops in neuroscience, where it is also known as active inference. The free energy principle models the behaviour of systems that are distinct from, but coupled to, another system (e.g., an embedding environment), where the degrees of freedom that implement the interface between the two systems is known as a Markov blanket. More ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bayesian Approaches To Brain Function
Bayesian approaches to brain function investigate the capacity of the nervous system to operate in situations of uncertainty in a fashion that is close to the optimal prescribed by Bayesian statistics. This term is used in behavioural sciences and neuroscience and studies associated with this term often strive to explain the brain's cognitive abilities based on statistical principles. It is frequently assumed that the nervous system maintains internal probabilistic models that are updated by neural processing of sensory information using methods approximating those of Bayesian probability. Origins This field of study has its historical roots in numerous disciplines including machine learning, experimental psychology and Bayesian statistics. As early as the 1860s, with the work of Hermann Helmholtz in experimental psychology the brain's ability to extract perceptual information from sensory data was modeled in terms of probabilistic estimation. The basic idea is that the nervous sys ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
