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Block World
The blocks world is a planning domain in artificial intelligence. It consists of a set of wooden blocks of various shapes and colors sitting on a table. The goal is to build one or more vertical stacks of blocks. Only one block may be moved at a time: it may either be placed on the table or placed atop another block. Because of this, any blocks that are, at a given time, under another block cannot be moved. Moreover, some kinds of blocks cannot have other blocks stacked on top of them. The simplicity of this toy world lends itself readily to classical symbolic artificial intelligence approaches, in which the world is modeled as a set of abstract symbols which may be reasoned about. Motivation Artificial Intelligence can be researched in theory and with practical applications. The problem with most practical application is, that the engineers don't know how to program an AI system. Instead of rejecting the challenge at all the idea is to invent an easy to solve domain which is c ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sandra Zilles
Sandra Zilles is a German and Canadian computer scientist, the Canada Research Chair in Computational Learning Theory at the University of Regina. Her research area encompasses machine learning and computational learning theory. Education and career Zilles was an undergraduate in Germany, at the Technical University of Kaiserslautern, where she earned a diploma in mathematics in 2000 and a Ph.D. in computer science in 2004. Her dissertation, ''Uniform Learning of Recursive Functions'', was jointly supervised by Rolf Wiehagen and Thomas Zeugmann. From 2004 to 2008 she was a senior researcher at the German Research Centre for Artificial Intelligence. In 2007 she began a postdoctoral research visit to the University of Alberta, and in 2009 she joined the University of Regina as an assistant professor. She was given a tier 2 Canada Research Chair in 2010, promoted to associate professor in 2013, and promoted again to full professor in 2019. In 2022 she was given a tier 1 Canada Researc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sussman Anomaly
The Sussman anomaly is a problem in artificial intelligence, first described by Gerald Sussman, that illustrates a weakness of noninterleaved planning algorithms, which were prominent in the early 1970s. Most modern planning systems are not restricted to noninterleaved planning and thus can handle this anomaly. While the significance/value of the problem is now a historical one, it is still useful for explaining why planning is non-trivial. In the problem, set in blocks world, three blocks (labeled A, B, and C) rest on a table. The agent must stack the blocks such that A is atop B, which in turn is atop C. However, it may only move one block at a time. The problem starts with B on the table, C atop A, and A on the table: However, noninterleaved planners typically separate the goal (stack A atop B atop C) into subgoals, such as: # get A atop B # get B atop C Suppose the planner starts by pursuing Goal 1. The straightforward solution is to move C out of the way, then move A atop ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gerald Jay Sussman
Gerald Jay Sussman (born February 8, 1947) is the Panasonic Professor of Electrical Engineering at the Massachusetts Institute of Technology (MIT). He has been involved in artificial intelligence (AI) research at MIT since 1964. His research has centered on understanding the problem-solving strategies used by scientists and engineers, with the goals of automating parts of the process and formalizing it to provide more effective methods of science and engineering education. Sussman has also worked in computer languages, in computer architecture, and in Very Large Scale Integration (VLSI) design. Education Sussman attended the Massachusetts Institute of Technology as an undergraduate and received his SB in mathematics in 1968. He continued his studies at MIT and obtained a PhD in 1973, also in mathematics, under the supervision of Seymour Papert. His doctoral thesis was titled "A Computational Model of Skill Acquisition" focusing on artificial intelligence and machine learning, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Patrick Winston
Patrick Henry Winston (February 5, 1943 – July 19, 2019) was an American computer scientist and professor at the Massachusetts Institute of Technology. Winston was director of the MIT Artificial Intelligence Laboratory from 1972 to 1997, succeeding Marvin Minsky, who left to help found the MIT Media Lab. Winston was succeeded as director by Rodney Brooks. After graduating from high school, Winston left East Peoria, a suburb of Peoria, IL, to come to MIT by train. He received his undergraduate degree from MIT in 1965, where he was a member of Phi Delta Theta fraternity, and went on to complete his Masters and PhD there as well, finalizing his PhD in 1970. His research interests included machine learning and human intelligence. Winston was known within the MIT community for his excellent teaching and strong commitment to supporting MIT undergraduate culture. At MIT, Winston taught 6.034: Artificial Intelligence and 6.803/6.833: Human Intelligence Enterprise. Winston's ''How to S ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
SHRDLU
SHRDLU is an early natural-language understanding computer program that was developed by Terry Winograd at MIT in 1968–1970. In the program, the user carries on a conversation with the computer, moving objects, naming collections and querying the state of a simplified " blocks world", essentially a virtual box filled with different blocks. SHRDLU was written in the Micro Planner and Lisp programming language on the DEC PDP-6 computer and a DEC graphics terminal. Later additions were made at the computer graphics labs at the University of Utah, adding a full 3D rendering of SHRDLU's "world". The name SHRDLU was derived from ETAOIN SHRDLU, the arrangement of the letter keys on a Linotype machine, arranged in descending order of usage frequency in English. Functionality SHRDLU is primarily a language parser that allows user interaction using English terms. The user instructs SHRDLU to move various objects around in the "blocks world" containing various basic objects: ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Terry Winograd
Terry Allen Winograd (born February 24, 1946) is an American computer scientist. He is a professor at Stanford University, and co-director of the Stanford Human–Computer Interaction Group. He is known within the philosophy of mind and artificial intelligence fields for his work on natural language using the SHRDLU program. Education Winograd grew up in Colorado and graduated from Colorado College in 1966. He wrote SHRDLU as a PhD thesis at MIT in the years from 1968–70. In making the program Winograd was concerned with the problem of providing a computer with sufficient "understanding" to be able to use natural language. Winograd built a blocks world, restricting the program's intellectual world to a simulated "world of toy blocks". The program could accept commands such as, "Find a block which is taller than the one you are holding and put it into the box" and carry out the requested action using a simulated block-moving arm. The program could also respond verbally, for exam ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dock Worker Robot
The word dock () in American English refers to one or a group of human-made structures that are involved in the handling of boats or ships (usually on or near a shore). In British English, the term is not used the same way as in American English; it is used to mean the area of water that is next to or around a wharf or quay. The exact meaning varies among different variants of the English language. "Dock" may also refer to a dockyard (also known as a shipyard) where the loading, unloading, building, or repairing of ships occurs. History The earliest known docks were those discovered in Wadi al-Jarf, an ancient Egyptian harbor, of Pharaoh Khufu, dating from c.2500 BC located on the Red Sea coast. Archaeologists also discovered anchors and storage jars near the site. A dock from Lothal in India dates from 2400 BC and was located away from the main current to avoid deposition of silt. Modern oceanographers have observed that the ancient Harappans must have possessed great kno ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
PDDL
The Planning Domain Definition Language (PDDL) is an attempt to standardize Artificial Intelligence (AI) planning languages. It was first developed by Drew McDermott and his colleagues in 1998 mainly to make the 1998/2000 International Planning Competition (IPC) possible, and then evolved with each competition. The standardization provided by PDDL has the benefit of making research more reusable and easily comparable, though at the cost of some expressive power, compared to domain-specific systems. Overview PDDL is a human-readable format for problems in automated planning that gives a description of the possible states of the world, a description of the set of possible actions, a specific initial state of the world, and a specific set of desired goals. Action descriptions include the prerequisites of the action and the effects of the action. PDDL separates the model of the planning problem into two major parts: (1) a domain description of those elements that are present in every ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Automated Planning And Scheduling
Automated planning and scheduling, sometimes denoted as simply AI planning, is a branch of artificial intelligence that concerns the realization of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles. Unlike classical control and classification problems, the solutions are complex and must be discovered and optimized in multidimensional space. Planning is also related to decision theory. In known environments with available models, planning can be done offline. Solutions can be found and evaluated prior to execution. In dynamically unknown environments, the strategy often needs to be revised online. Models and policies must be adapted. Solutions usually resort to iterative trial and error processes commonly seen in artificial intelligence. These include dynamic programming, reinforcement learning and combinatorial optimization. Languages used to describe planning and scheduling are often called action language ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Search Problem
In computational complexity theory and computability theory, a search problem is a computational problem of finding an ''admissible'' answer for a given input value, provided that such an answer exists. In fact, a search problem is specified by a binary relation where if and only if "'' is an admissible answer given ''". Search problems frequently occur in graph theory and combinatorial optimization, e.g. searching for matchings, optional cliques, and stable sets in a given undirected graph. An algorithm is said to solve a search problem if, for every input value , it returns an admissible answer for when such an answer exists; otherwise, it returns any appropriate output, e.g. "not found" for with no such answer. Definition PlanetMath defines the problem as follows: If R is a binary relation such that \operatorname(R)\subseteq\Gamma^ and T is a Turing machine, then T calculates f if: * If x is such that there is some y such that R(x,y) then T accepts x with output z suc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
NP-hard
In computational complexity theory, a computational problem ''H'' is called NP-hard if, for every problem ''L'' which can be solved in non-deterministic polynomial-time, there is a polynomial-time reduction from ''L'' to ''H''. That is, assuming a solution for ''H'' takes 1 unit time, ''H''s solution can be used to solve ''L'' in polynomial time. As a consequence, finding a polynomial time algorithm to solve a single NP-hard problem would give polynomial time algorithms for all the problems in the complexity class NP. As it is suspected, but unproven, that P≠NP, it is unlikely that any polynomial-time algorithms for NP-hard problems exist. A simple example of an NP-hard problem is the subset sum problem. Informally, if ''H'' is NP-hard, then it is at least as difficult to solve as the problems in NP. However, the opposite direction is not true: some problems are undecidable, and therefore even more difficult to solve than all problems in NP, but they are probably not NP- ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
