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Peter Dayan
Peter Dayan is director at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany. He is co-author of ''Theoretical Neuroscience'', an influential textbook on computational neuroscience. He is known for applying Bayesian methods from machine learning and artificial intelligence to understand neural function and is particularly recognized for relating neurotransmitter levels to prediction errors and Bayesian uncertainties. He has pioneered the field of reinforcement learning (RL) where he helped develop the Q-learning algorithm, and made contributions to unsupervised learning, including the wake-sleep algorithm for neural networks and the Helmholtz machine. Education Dayan studied mathematics at the University of Cambridge and then continued for a PhD in artificial intelligence at the University of Edinburgh School of Informatics on statistical learning supervised by David Willshaw and David Wallace, focusing on associative memory and reinforcement learn ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
University Of Edinburgh School Of Informatics
The School of Informatics is an academic unit of the University of Edinburgh, in Scotland, responsible for research, teaching, outreach and commercialisation in informatics. It was created in 1998 from the former Department of Artificial Intelligence, the Centre for Cognitive Science and the Department of Computer Science, along with the Artificial Intelligence Applications Institute (AIAI) and the Human Communication Research Centre. Research in the School of Informatics draws on multiple disciplines. The school is particularly known for research in the areas of artificial intelligence, computational linguistics, systems biology, mathematical logic and theoretical computer science; but also contributes to many other areas of informatics. The School of Informatics was ranked 12th in the world by the QS World University Rankings 2014. As of 2022, the school is ranked 1st in the UK according to ''CSRankings'', 1st in the UK in the latest 2021 Research Excellence Framework (REF) by ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computational Neuroscience
Computational neuroscience (also known as theoretical neuroscience or mathematical neuroscience) is a branch of neuroscience which employs mathematical models, computer simulations, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology and cognitive abilities of the nervous system. Computational neuroscience employs computational simulations to validate and solve mathematical models, and so can be seen as a sub-field of theoretical neuroscience; however, the two fields are often synonymous. The term mathematical neuroscience is also used sometimes, to stress the quantitative nature of the field. Computational neuroscience focuses on the description of biologically plausible neurons (and neural systems) and their physiology and dynamics, and it is therefore not directly concerned with biologically unrealistic models used in connectionism, control theory, cybernetics, quantitative psychology, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Tübingen
Tübingen (, , Swabian: ''Dibenga'') is a traditional university city in central Baden-Württemberg, Germany. It is situated south of the state capital, Stuttgart, and developed on both sides of the Neckar and Ammer rivers. about one in three of the 90,000 people living in Tübingen is a student. As of the 2018/2019 winter semester, 27,665 students attend the Eberhard Karls University of Tübingen. The city has the lowest median age in Germany, in part due to its status as a university city. As of December 31, 2015, the average age of a citizen of Tübingen is 39.1 years. The city is known for its veganism and environmentalism. Immediately north of the city lies the Schönbuch, a densely wooded nature park. The Swabian Alb mountains rise about (beeline Tübingen City to Roßberg - 869 m) to the southeast of Tübingen. The Ammer and Steinlach rivers are tributaries of the Neckar river, which flows in an easterly direction through the city, just south of the medieval old t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Association (psychology)
Association in psychology refers to a mental connection between concepts, events, or mental states that usually stems from specific experiences.Klein, Stephen (2012). ''Learning: Principles and Applications'' (6 ed.). SAGE Publications. . 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.Boring, E. G. (1950) It finds its place in modern psychology in such areas as memory, learning, and the study of neural pathways. Learned associations Associative learning is when a subject creates a relationship between stimuli (e.g. auditory or visual) or behavior and the original stimulus. The higher the concreteness of stimulus items, the more likely are they to evoke sensor ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
David Wallace (physicist)
Sir David James Wallace, CBE, FRS, FRSE, FREng (born 7 October 1945) is a British physicist and academic. He was the Vice-Chancellor of Loughborough University from 1994 to 2005, and the Master of Churchill College, Cambridge from 2006 to 2014. Early life and education Wallace was born on 7 October 1945. He was educated at Hawick High School in Hawick, Borders, Scotland and went to the University of Edinburgh where he earned a degree in Mathematical Physics and a PhD in Elementary particle theory, under the supervision of Peter Higgs. Career After postdoctoral research work as a Harkness Fellow at Princeton University, Wallace became a physics lecturer at the University of Southampton in 1972. In 1979 he became the fourth Tait Professor of Mathematical Physics at the University of Edinburgh, succeeding Nicholas Kemmer. He won the James Clerk Maxwell Medal and Prize in 1980. He became Director of the Edinburgh Parallel Computing Centre (EPCC) and in 1996 he was appointed ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Helmholtz Machine
Hermann Ludwig Ferdinand von Helmholtz (31 August 1821 – 8 September 1894) was a German physicist and physician who made significant contributions in several scientific fields, particularly hydrodynamic stability. The Helmholtz Association, the largest German association of research institutions, is named in his honor. In the fields of physiology and psychology, Helmholtz is known for his mathematics concerning the eye, theories of vision, ideas on the visual perception of space, color vision research, the sensation of tone, perceptions of sound, and empiricism in the physiology of perception. In physics, he is known for his theories on the conservation of energy, work in electrodynamics, chemical thermodynamics, and on a mechanical foundation of thermodynamics. As a philosopher, he is known for his philosophy of science, ideas on the relation between the laws of perception and the laws of nature, the science of aesthetics, and ideas on the civilizing power of science. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Neural Network
A neural network is a network or circuit of biological neurons, or, in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus, a neural network is either a biological neural network, made up of biological neurons, or an artificial neural network, used for solving artificial intelligence (AI) problems. The connections of the biological neuron are modeled in artificial neural networks as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed. This activity is referred to as a linear combination. Finally, an activation function controls the amplitude of the output. For example, an acceptable range of output is usually between 0 and 1, or it could be −1 and 1. These artificial networks may be used for predictive modeling, adaptive control and applications where they can be trained via a dataset. Self-learning resulting from e ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Wake-sleep Algorithm
The wake-sleep algorithm is an unsupervised learning algorithm for a stochastic multilayer neural network. The algorithm adjusts the parameters so as to produce a good density estimator. There are two learning phases, the “wake” phase and the “sleep” phase, which are performed alternately. It was first designed as a model for brain functioning using variational Bayesian learning. After that, the algorithm was adapted to machine learning. It can be viewed as a way to train a Helmholtz Machine. It can also be used in Deep Belief Networks (DBN). Description The wake-sleep algorithm is visualized as a stack of layers containing representations of data. Layers above represent data from the layer below it. Actual data is placed below the bottom layer, causing layers on top of it to become gradually more abstract. Between each pair of layers there is a recognition weight and generative weight, which are trained to improve reliability during the algorithm runtime. The wake-sle ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Unsupervised Learning
Unsupervised learning is a type of algorithm that learns patterns from untagged data. The hope is that through mimicry, which is an important mode of learning in people, the machine is forced to build a concise representation of its world and then generate imaginative content from it. In contrast to supervised learning where data is tagged by an expert, e.g. tagged as a "ball" or "fish", unsupervised methods exhibit self-organization that captures patterns as probability densities or a combination of neural feature preferences encoded in the machine's weights and activations. The other levels in the supervision spectrum are reinforcement learning where the machine is given only a numerical performance score as guidance, and semi-supervised learning where a small portion of the data is tagged. Neural networks Tasks vs. methods Neural network tasks are often categorized as discriminative (recognition) or generative (imagination). Often but not always, discriminative tas ... [...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] |
Neurotransmitter
A neurotransmitter is a signaling molecule secreted by a neuron to affect another cell across a synapse. The cell receiving the signal, any main body part or target cell, may be another neuron, but could also be a gland or muscle cell. Neurotransmitters are released from synaptic vesicles into the synaptic cleft where they are able to interact with neurotransmitter receptors on the target cell. The neurotransmitter's effect on the target cell is determined by the receptor it binds. Many neurotransmitters are synthesized from simple and plentiful precursors such as amino acids, which are readily available and often require a small number of biosynthetic steps for conversion. Neurotransmitters are essential to the function of complex neural systems. The exact number of unique neurotransmitters in humans is unknown, but more than 100 have been identified. Common neurotransmitters include glutamate, GABA, acetylcholine, glycine and norepinephrine. Mechanism and cycle Synthes ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial Intelligence
Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech recognition, computer vision, translation between (natural) languages, as well as other mappings of inputs. The ''Oxford English Dictionary'' of Oxford University Press defines artificial intelligence as: the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. AI applications include advanced web search engines (e.g., Google), recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Tesla), automated decision-making and competing at the highest level in strategic game systems (such as chess and Go). ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
