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Partially Observable
A partially observable system is one in which the entire state of the system is not fully visible to an external sensor. In a partially observable system the observer may utilise a memory system in order to add information to the observer's understanding of the system.Peter Norvig, Sebastian Thrun. UdacityIntroduction to Artificial Intelligence/ref> An example of a partially observable system would be a card game in which some of the cards are discarded into a pile face down. In this case the observer is only able to view their own cards and potentially those of the dealer. They are not able to view the face-down (used) cards, nor the cards that will be dealt at some stage in the future. A memory system can be used to remember the previously dealt cards that are now on the used pile. This adds to the total sum of knowledge that the observer can use to make decisions. In contrast, a fully observable system would be that of chess. In chess (apart from the 'who is moving next' stat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sensor
A sensor is often defined as a device that receives and responds to a signal or stimulus. The stimulus is the quantity, property, or condition that is sensed and converted into electrical signal. In the broadest definition, a sensor is a device, module, machine, or subsystem that detects events or changes in its environment and sends the information to other electronics, frequently a computer processor. Sensors are used in everyday objects such as touch-sensitive elevator buttons ( tactile sensor) and lamps which dim or brighten by touching the base, and in innumerable applications of which most people are never aware. With advances in micromachinery and easy-to-use microcontroller platforms, the uses of sensors have expanded beyond the traditional fields of temperature, pressure and flow measurement, for example into MARG sensors. Analog sensors such as potentiometers and force-sensing resistors are still widely used. Their applications include manufacturing and machinery ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Peter Norvig
Peter Norvig (born 14 December 1956) is an American computer scientist and Distinguished Education Fellow at the Stanford Institute for Human-Centered AI. He previously served as a director of research and search quality at Google. Norvig is the co-author with Stuart J. Russell of the most popular textbook in the field of AI: '' Artificial Intelligence: A Modern Approach'' used in more than 1,500 universities in 135 countries. Early life and education Norvig grew up in an academic family. His father was Danish and came to the United States after World War II to study math at the University of Minnesota. Norvig received a Bachelor of Science in applied mathematics from Brown University and a Ph.D. in computer science from the University of California, Berkeley. Career and research Norvig is a councilor of the Association for the Advancement of Artificial Intelligence and co-author, with Stuart J. Russell, of '' Artificial Intelligence: A Modern Approach'', now the leading col ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sebastian Thrun
Sebastian Thrun (born May 14, 1967) is a German-American entrepreneur, educator, and computer scientist. He is chief executive officer of Kitty Hawk Corporation, and chairman and co-founder of Udacity. Before that, he was a Google vice president and Fellow, a Professor of Computer Science at Stanford University, and before that at Carnegie Mellon University. At Google, he co-founded Google X along with Yoky Matsuoka and Anthony Levandowski and Google's self-driving car team with Anthony Levandowski. He is also an adjunct professor at Stanford University and at Georgia Tech. Thrun led development of the robotic vehicle Stanley which won the 2005 DARPA Grand Challenge, and which has since been placed on exhibit in the Smithsonian Institution's National Museum of American History. His team also developed a vehicle called Junior, which placed second at the DARPA Urban Challenge in 2007. Thrun led the development of the Google self-driving car. Thrun is also well known for ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Udacity
Udacity, Inc. is an American global for-profit massive open online course provider. It was founded by Sebastian Thrun, David Stavens, and Mike Sokolsky offering massive open online courses. According to Thrun, the origin of the name Udacity comes from the company's desire to be "audacious for you, the student". While it originally focused on offering university-style courses, it now focuses more on vocational education, vocational courses for professionals. Accenture agreed to acquire the company in March 2024. History Udacity is the outgrowth of free computer science classes offered in 2011 through Stanford University. Thrun has stated he hopes half a million students will enroll, after an enrollment of 160,000 students in the predecessor course at Stanford, Introduction to Artificial Intelligence, and 90,000 students had enrolled in the initial two classes . Udacity was announced at the 2012 Digital Life Design conference. Udacity is funded by venture capital firm, Charles R ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Card Game
A card game is any game that uses playing cards as the primary device with which the game is played, whether the cards are of a traditional design or specifically created for the game (proprietary). Countless card games exist, including families of related games (such as poker). A small number of card games played with traditional decks have formally standardized rules with international tournaments being held, but most are folk games whose rules may vary by region, culture, location or from circle (cards), circle to circle. Traditional card games are played with a ''deck'' or ''pack'' of playing cards which are identical in size and shape. Each card has two sides, the ''face'' and the ''back''. Normally the backs of the cards are indistinguishable. The faces of the cards may all be unique, or there can be duplicates. The composition of a deck is known to each player. In some cases several decks are Shuffling, shuffled together to form a single ''pack'' or ''shoe''. Modern car ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Chess
Chess is a board game for two players. It is an abstract strategy game that involves Perfect information, no hidden information and no elements of game of chance, chance. It is played on a square chessboard, board consisting of 64 squares arranged in an 8×8 grid. The players, referred to as White and Black in chess, "White" and "Black", each control sixteen Chess piece, pieces: one king (chess), king, one queen (chess), queen, two rook (chess), rooks, two bishop (chess), bishops, two knight (chess), knights, and eight pawn (chess), pawns, with each type of piece having a different pattern of movement. An enemy piece may be captured (removed from the board) by moving one's own piece onto the square it occupies. The object of the game is to "checkmate" (threaten with inescapable capture) the enemy king. There are also several ways a game can end in a draw (chess), draw. The recorded history of chess goes back to at least the emergence of chaturanga—also thought to be an ancesto ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Partially Observable Markov Decision Process
A partially observable Markov decision process (POMDP) is a generalization of a Markov decision process (MDP). A POMDP models an agent decision process in which it is assumed that the system dynamics are determined by an MDP, but the agent cannot directly observe the underlying state. Instead, it must maintain a sensor model (the probability distribution of different observations given the underlying state) and the underlying MDP. Unlike the policy function in MDP which maps the underlying states to the actions, POMDP's policy is a mapping from the history of observations (or belief states) to the actions. The POMDP framework is general enough to model a variety of real-world sequential decision processes. Applications include robot navigation problems, machine maintenance, and planning under uncertainty in general. The general framework of Markov decision processes with imperfect information was described by Karl Johan Åström in 1965 in the case of a discrete state space, and i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
