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Intrinsic Motivation (artificial Intelligence)
Intrinsic motivation in the study of artificial intelligence and robotics is a mechanism for enabling artificial agents (including robots) to exhibit inherently rewarding behaviours such as exploration and curiosity, grouped under the same term in the study of psychology. Psychologists consider intrinsic motivation in humans to be the drive to perform an activity for inherent satisfaction – just for the fun or challenge of it. Definition An intelligent agent is intrinsically motivated to act if the information content alone, or the experience resulting from the action, is the motivating factor. Information content in this context is measured in the information-theoretic sense of quantifying uncertainty. A typical intrinsic motivation is to search for unusual, surprising situations (exploration), in contrast to a typical extrinsic motivation such as the search for food (homeostasis). Extrinsic motivations are typically described in artificial intelligence as ''task-dependent'' ... [...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] |
Exploration Problem
In robotics, the exploration problem deals with the use of a robot to maximize the knowledge over a particular area. The exploration problem arises in robotic mapping and search & rescue situations, where an environment might be dangerous or inaccessible to humans. Overview The exploration problem naturally arises in situations in which a robot is utilized to survey an area that is dangerous or inaccessible for humans. The field of robotic explorations draws from various fields of information gathering and decision theory, and have been studied as far back as the 1950s. The earliest work in robotic exploration was done in the context of simple finite state automata known as bandits, where algorithms were designed to distinguish and map different states in a finite state automaton. Since then, the primary emphasis has been shifted to the robotics system development domain, where exploration-algorithms guided robot have been used to survey volcanos, search and rescue, and abandon ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Motivation
Motivation is the reason for which humans and other animals initiate, continue, or terminate a behavior at a given time. Motivational states are commonly understood as forces acting within the agent that create a disposition to engage in goal-directed behavior. It is often held that different mental states compete with each other and that only the strongest state determines behavior. This means that we can be motivated to do something without actually doing it. The paradigmatic mental state providing motivation is desire. But various other states, such as beliefs about what one ought to do or intentions, may also provide motivation. Motivation is derived from the word 'motive', which denotes a person's needs, desires, wants, or urges. It is the process of motivating individuals to take action in order to achieve a goal. The psychological elements fueling people's behavior in the context of job goals might include a desire for money. Various competing theories have been proposed co ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gary Marcus
Gary F. Marcus (born February 8, 1970) is a professor emeritus of psychology and neural science at New York University. In 2014 he founded Geometric Intelligence, a machine-learning company later acquired by Uber. Marcus's books include '' Guitar Zero,'' which appeared on the ''New York Times'' Best Seller list, and ''Kluge,'' which was a ''New York Times'' Editors' Choice. Marcus challenges connectionist theories which rely on random connections and argues instead that neurons can be put together into circuits that do things such as process rules or process structured representations. He hypothesizes that a small number of genes account for the functioning of the intricate human brain. He criticizes the use of massive amounts of data to build artificial intelligence systems, arguing: "If we are to build artificial general intelligence, we are going to need to learn something from humans, how they reason and understand the physical world, and how they represent and acquire lang ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
AlphaGo
AlphaGo is a computer program that plays the board game Go (game), Go. It was developed by DeepMind Technologies a subsidiary of Google (now Alphabet Inc.). Subsequent versions of AlphaGo became increasingly powerful, including a version that competed under the name AlphaGo Master, Master. After retiring from competitive play, AlphaGo Master was succeeded by an even more powerful version known as AlphaGo Zero, which was completely Self-play (reinforcement learning technique), self-taught without learning from human games. AlphaGo Zero was then generalized into a program known as AlphaZero, which played additional games, including chess and shogi. AlphaZero has in turn been succeeded by a program known as MuZero which learns without being taught the rules. AlphaGo and its successors use a Monte Carlo tree search algorithm to find its moves based on knowledge previously acquired by machine learning, specifically by an artificial neural network (a deep learning method) by extensi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Deep Learning
Deep learning (also known as deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised. Deep-learning architectures such as deep neural networks, deep belief networks, deep reinforcement learning, recurrent neural networks, convolutional neural networks and Transformers have been applied to fields including computer vision, speech recognition, natural language processing, machine translation, bioinformatics, drug design, medical image analysis, Climatology, climate science, material inspection and board game programs, where they have produced results comparable to and in some cases surpassing human expert performance. Artificial neural networks (ANNs) were inspired by information processing and distributed communication nodes in biological systems. ANNs have various differences from biological brains. Specifically, artificial ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Developmental Robotics
Developmental robotics (DevRob), sometimes called epigenetic robotics, is a scientific field which aims at studying the developmental mechanisms, architectures and constraints that allow lifelong and open-ended learning of new skills and new knowledge in embodied machines. As in human children, learning is expected to be cumulative and of progressively increasing complexity, and to result from self-exploration of the world in combination with social interaction. The typical methodological approach consists in starting from theories of human and animal development elaborated in fields such as developmental psychology, neuroscience, developmental and evolutionary biology, and linguistics, then to formalize and implement them in robots, sometimes exploring extensions or variants of them. The experimentation of those models in robots allows researchers to confront them with reality, and as a consequence, developmental robotics also provides feedback and novel hypotheses on theories of hu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Flow (psychology)
In positive psychology, a flow state, also known colloquially as being in the zone, is the mental state in which a person performing some activity is fully immersed in a feeling of energized focus, full involvement, and enjoyment in the process of the activity. In essence, flow is characterized by the complete absorption in what one does, and a resulting transformation in one's sense of time. Flow is the melting together of action and consciousness; the state of finding a balance between a skill and how challenging that task is. It requires a high level of concentration, however, it should be effortless. Flow is used as a coping skill for stress and anxiety when productively pursuing a form of leisure that matches one's skill set. Named by the psychologist Mihály Csíkszentmihályi in 1975, the concept has been widely referred to across a variety of fields (and is particularly well recognized in occupational therapy), though the concept has been claimed to have existed for thou ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Luc Steels
Luc Steels (born in 1952) is a Belgium, Belgian scientist and artist. Steels is considered a pioneer of Artificial intelligence, Artificial Intelligence in Europe who has made contributions to expert systems, behavior based robotics, behavior-based robotics, artificial life and evolutionary computational linguistics. He was a fellow of the Catalan Institution for Research and Advanced Studies ICREA associated as a research professor with the Institute for Evolutionary Biology (UPF/CSIC) in Barcelona. He was formerly founding Director of the Artificial Intelligence Laboratory of the Vrije Universiteit Brussel and founding director of the Sony Computer Science Laboratory in Paris. Steels has also been active in the arts collaborating with visual artists and theater makers and composing music for opera. Biography Steels obtained a master's degree in Computer Science at MIT, specializing in AI under the supervision of Marvin Minsky and Carl Hewitt. He obtained a Ph.D. at the Univers ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Empowerment (artificial Intelligence)
Empowerment in the field of artificial intelligence formalises and quantifies (via information theory) the potential an agent perceives that it has to influence its environment. An agent which follows an empowerment maximising policy, acts to maximise future options (typically up to some limited horizon). Empowerment can be used as a (pseudo) utility function that depends only on information gathered from the local environment to guide action, rather than seeking an externally imposed goal, thus is a form of intrinsic motivation. The empowerment formalism depends on a probabilistic model commonly used in artificial intelligence. An autonomous agent operates in the world by taking in sensory information and acting to change its state, or that of the environment, in a cycle of perceiving and acting known as the perception-action loop. Agent state and actions are modelled by random variables (S: s \in \mathcal, A: a \in \mathcal) and time (t). The choice of action depends on the curr ... [...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] |
