University of Maryland, College Park
The University of Maryland, College Park is a public research university in College Park, Maryland. Founded in 1856, UMD is the flagship institution of the University System of Maryland, is the largest university in both the state and the Washington metropolitan area, with more than 41,000 students representing all fifty states and 123 countries, a global alumni network of over 360,000, its twelve schools and colleges together offer over 200 degree-granting programs, including 92 undergraduate majors, 107 master's programs, 83 doctoral programs. UMD is a member of the Association of American Universities and competes in intercollegiate athletics as a member of the Big Ten Conference; the University of Maryland's proximity to the nation's capital has resulted in many research partnerships with the federal government. It is classified as one of 115 first tier research universities in the country by the Carnegie Foundation, is labeled a "Public Ivy", denoting a quality of education comparable to the private Ivy League.
UMD is ranked among the top 100 universities both nationally and globally by several indices. In 2016, the University of Maryland, College Park and the University of Maryland, Baltimore formalized their strategic partnership after their collaboration created more innovative medical and educational programs, as well as greater research grants and joint faculty appointments than either campus has been able to accomplish on its own; as of 2017, the operating budget of the University of Maryland is $2.1 billion. For the 2018 fiscal year, the university received a total of over $545 million in external research funding. In October 2017, the university received a record-breaking donation of $219.5 million from the A. James & Alice B. Clark Foundation, ranking among the largest philanthropic gifts to a public university in the country. On March 6, 1856, the forerunner of today's University of Maryland was chartered as the Maryland Agricultural College. Two years Charles Benedict Calvert, a future U.
S. Representative from the sixth congressional district of Maryland, 1861-1863, during the American Civil War and descendent of the first Lord Baltimores, colonial proprietors of the Province of Maryland in 1634, purchased 420 acres of the Riversdale Mansion estate nearby today's College Park, Maryland; that year, Calvert founded the school and was the acting president from 1859 to 1860. On October 5, 1859, the first 34 students entered the Maryland Agricultural College; the school became a land grant college in February 1864. During the Civil War, Confederate soldiers under Brigadier General Bradley Tyler Johnson moved past the college on July 12, 1864 as part of Jubal Early's raid on Washington, D. C. By the end of the war, financial problems forced the administrators to sell off 200 acres of land, the continuing decline in enrollment sent the Maryland Agricultural College into bankruptcy. For the next two years the campus was used as a boys preparatory school. Following the Civil War, in February 1866 the Maryland legislature assumed half ownership of the school.
The college thus became in part a state institution. By October 1867, the school reopened with 11 students. In the next six years, enrollment grew and the school's debt was paid off. In 1873, Samuel Jones, a former Confederate Major General, became president of the college. Twenty years the federally funded Agricultural Experiment Station was established there. During the same period, state laws granted the college regulatory powers in several areas—including controlling farm disease, inspecting feed, establishing a state weather bureau and geological survey, housing the board of forestry. Morrill Hall was built the following year. On November 29, 1912, a fire destroyed the barracks where the students were housed, all the school's records, most of the academic buildings, leaving only Morrill Hall untouched. There were no injuries or fatalities, all but two students returned to the university and insisted on classes continuing. Students were housed by families in neighboring towns until housing could be rebuilt, although a new administration building was not built until the 1940s.
A large brick and concrete compass inlaid in the ground designates the former center of campus as it existed in 1912. The state took control of the school in 1916, the institution was renamed Maryland State College; that year, the first female students enrolled at the school. On April 9, 1920, the college became part of the existing University of Maryland, replacing St. John's College, Annapolis as the University's undergraduate campus. In the same year, the graduate school on the College Park campus awarded its first PhD degrees and the university's enrollment reached 500 students. In 1925 the university was accredited by the Association of American Universities. By the time the first black students enrolled at the university in 1951, enrollment had grown to nearly 10,000 students—4,000 of whom were women. Prior to 1951, many black students in Maryland were enrolled at the University of Maryland, Eastern Shore. In 1957, President Wilson H. Elkins made a push to increase academic standards at the university.
His efforts resulted in the creation of one of the first Academic Probation Plans. The first year the plan went into effect, 1,550 students (18% of the total student body
In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of achieving its goals. Colloquially, the term "artificial intelligence" is used to describe machines that mimic "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving"; as machines become capable, tasks considered to require "intelligence" are removed from the definition of AI, a phenomenon known as the AI effect. A quip in Tesler's Theorem says "AI is whatever hasn't been done yet." For instance, optical character recognition is excluded from things considered to be AI, having become a routine technology. Modern machine capabilities classified as AI include understanding human speech, competing at the highest level in strategic game systems, autonomously operating cars, intelligent routing in content delivery networks and military simulations.
Artificial intelligence can be classified into three different types of systems: analytical, human-inspired, humanized artificial intelligence. Analytical AI has only characteristics consistent with cognitive intelligence. Human-inspired AI has elements from emotional intelligence. Humanized AI shows characteristics of all types of competencies, is able to be self-conscious and is self-aware in interactions with others. Artificial intelligence was founded as an academic discipline in 1956, in the years since has experienced several waves of optimism, followed by disappointment and the loss of funding, followed by new approaches and renewed funding. For most of its history, AI research has been divided into subfields that fail to communicate with each other; these sub-fields are based on technical considerations, such as particular goals, the use of particular tools, or deep philosophical differences. Subfields have been based on social factors; the traditional problems of AI research include reasoning, knowledge representation, learning, natural language processing and the ability to move and manipulate objects.
General intelligence is among the field's long-term goals. Approaches include statistical methods, computational intelligence, traditional symbolic AI. Many tools are used in AI, including versions of search and mathematical optimization, artificial neural networks, methods based on statistics and economics; the AI field draws upon computer science, information engineering, psychology, linguistics and many other fields. The field was founded on the claim that human intelligence "can be so described that a machine can be made to simulate it"; this raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence which are issues that have been explored by myth and philosophy since antiquity. Some people consider AI to be a danger to humanity if it progresses unabated. Others believe that AI, unlike previous technological revolutions, will create a risk of mass unemployment. In the twenty-first century, AI techniques have experienced a resurgence following concurrent advances in computer power, large amounts of data, theoretical understanding.
Thought-capable artificial beings appeared as storytelling devices in antiquity, have been common in fiction, as in Mary Shelley's Frankenstein or Karel Čapek's R. U. R.. These characters and their fates raised many of the same issues now discussed in the ethics of artificial intelligence; the study of mechanical or "formal" reasoning began with philosophers and mathematicians in antiquity. The study of mathematical logic led directly to Alan Turing's theory of computation, which suggested that a machine, by shuffling symbols as simple as "0" and "1", could simulate any conceivable act of mathematical deduction; this insight, that digital computers can simulate any process of formal reasoning, is known as the Church–Turing thesis. Along with concurrent discoveries in neurobiology, information theory and cybernetics, this led researchers to consider the possibility of building an electronic brain. Turing proposed that "if a human could not distinguish between responses from a machine and a human, the machine could be considered "intelligent".
The first work, now recognized as AI was McCullouch and Pitts' 1943 formal design for Turing-complete "artificial neurons". The field of AI research was born at a workshop at Dartmouth College in 1956. Attendees Allen Newell, Herbert Simon, John McCarthy, Marvin Minsky and Arthur Samuel became the founders and leaders of AI research, they and their students produced programs that the press described as "astonishing": computers were learning checkers strategies (and by 1959 were playing better than the average human
SRI International is an American nonprofit scientific research institute and organization headquartered in Menlo Park, California. The trustees of Stanford University established SRI in 1946 as a center of innovation to support economic development in the region; the organization was founded as the Stanford Research Institute. SRI formally separated from Stanford University in 1970 and became known as SRI International in 1977. SRI performs client-sponsored research and development for government agencies, commercial businesses, private foundations, it licenses its technologies, forms strategic partnerships, sells products, creates spin-off companies. SRI's annual revenue in 2014 was $540 million. SRI's headquarters are located near the Stanford University campus. William A. Jeffrey has served as SRI's president and CEO since September 2014. SRI employs about 2,100 people. Sarnoff Corporation, a wholly owned subsidiary of SRI since 1988, was integrated into SRI in January 2011. SRI's focus areas include biomedical sciences and materials, computing and space systems, economic development and learning, energy and environmental technology and national defense, as well as sensing and devices.
SRI has received more than 4,000 patent applications worldwide. In the 1920s, Stanford University professor Robert E. Swain proposed creating a research institute in the Western United States. Herbert Hoover a trustee of Stanford University, was an early proponent of an institute, but became less involved with the project after he was elected president of the United States; the development of the institute was delayed by the Great Depression in the 1930s and World War II in the 1940s, with three separate attempts leading to its formation in 1946. In August 1945, Maurice Nelles, Morlan A. Visel, Ernest L. Black of Lockheed made the first attempt to create the institute with the formation of the "Pacific Research Foundation" in Los Angeles. A second attempt was made by Henry T. Heald president of the Illinois Institute of Technology. In 1945, Heald wrote a report recommending a research institute on the West Coast and a close association with Stanford University with an initial grant of $500,000.
A third attempt was made by Stanford University's dean of engineering. Terman's proposal followed Heald's, but focused on faculty and student research more than contract research; the trustees of Stanford University voted to create the organization in 1946. It was structured so that its goals were aligned with the charter of the university—to advance scientific knowledge and to benefit the public at large, not just the students of Stanford University; the trustees were named as the corporation's general members, elected SRI's directors. Research chemist William F. Talbot became the first director of the institute. Stanford University president Donald Tresidder instructed Talbot to avoid work that would conflict with the interests of the university federal contracts that might attract political pressure; the drive to find work and the lack of support from Stanford faculty caused the new research institute to violate this directive six months through the pursuit of a contract with the Office of Naval Research.
This and other issues, including frustration with Tresidder's micromanagement of the new organization, caused Talbot to offer his resignation, which Tresidder accepted. Talbot was replaced by Jesse Hobson, who had led the Armour Research Foundation, but the pursuit of contract work remained. SRI's first research project investigated whether the guayule plant could be used as a source of natural rubber. During World War II, rubber was imported into the U. S. and was subject to strict rationing. From 1942 to 1946, the United States Department of Agriculture supported a project to create a domestic source of natural rubber. Once the war ended, the United States Congress cut funding for the program. SRI's first economic study was for the United States Air Force. In 1947, the Air Force wanted to determine the expansion potential of the U. S. aircraft industry. In 1948, SRI began research and consultation with Chevron Corporation to develop an artificial substitute for tallow and coconut oil in soap production.
Procter & Gamble used the substance as the basis for Tide laundry detergent. The institute performed much of the early research on air pollution and the formation of ozone in the lower atmosphere. SRI sponsored the First National Air Pollution Symposium in Pasadena, California, in November 1949. Experts gave presentations on pollution research, exchanged ideas and techniques, stimulated interest in the field; the event was attended by 400 scientists, business executives, civic leaders from the U. S. SRI co-sponsored subsequent events on the subject. In April 1953, Walt and Roy Disney hired SRI to consult on their proposal for establishing an amusement park in Burbank, California. SRI provided information on location, attendance patterns, economic feasibility. SRI selected a larger site in Anaheim, prepared reports about operation, provided on-site administrative support for Disneyland and acted in an advisory role as the park expanded. In 1955, SRI was c
Hierarchical control system
A hierarchical control system is a form of control system in which a set of devices and governing software is arranged in a hierarchical tree. When the links in the tree are implemented by a computer network that hierarchical control system is a form of networked control system. A human-built system with complex behavior is organized as a hierarchy. For example, a command hierarchy has among its notable features the organizational chart of superiors and lines of organizational communication. Hierarchical control systems are organized to divide the decision making responsibility; each element of the hierarchy is a linked node in the tree. Commands and goals to be achieved flow down the tree from superior nodes to subordinate nodes, whereas sensations and command results flow up the tree from subordinate to superior nodes. Nodes may exchange messages with their siblings; the two distinguishing features of a hierarchical control system are related to its layers. Each higher layer of the tree operates with a longer interval of planning and execution time than its lower layer.
The lower layers have local tasks and sensations, their activities are planned and coordinated by higher layers which do not override their decisions. The layers form a hybrid intelligent system in which reactive layers are sub-symbolic; the higher layers, having relaxed time constraints, are capable of reasoning from an abstract world model and performing planning. A hierarchical task network is a good fit for planning in a hierarchical control system. Besides artificial systems, an animal's control systems are proposed to be organized as a hierarchy. In perceptual control theory, which postulates that an organism's behavior is a means of controlling its perceptions, the organism's control systems are suggested to be organized in a hierarchical pattern as their perceptions are constructed so; the accompanying diagram is a general hierarchical model which shows functional manufacturing levels using computerised control of an industrial control system. Referring to the diagram. Level 2 contains the supervisory computers, which collate information from processor nodes on the system, provide the operator control screens.
Level 3 is the production control level, which does not directly control the process, but is concerned with monitoring production and monitoring targets Level 4 is the production scheduling level. Among the robotic paradigms is the hierarchical paradigm in which a robot operates in a top-down fashion, heavy on planning motion planning. Computer-aided production engineering has been a research focus at NIST since the 1980s, its Automated Manufacturing Research Facility was used to develop a five layer production control model. In the early 1990s DARPA sponsored research to develop distributed intelligent control systems for applications such as military command and control systems. NIST built on earlier research to develop its Real-Time Control System and Real-time Control System Software, a generic hierarchical control system, used to operate a manufacturing cell, a robot crane, an automated vehicle. In November 2007, DARPA held the Urban Challenge; the winning entry, Tartan Racing employed a hierarchical control system, with layered mission planning, motion planning, behavior generation, world modelling, mechatronics.
Subsumption architecture is a methodology for developing artificial intelligence, associated with behavior based robotics. This architecture is a way of decomposing complicated intelligent behavior into many "simple" behavior modules, which are in turn organized into layers; each layer implements a particular goal of the software agent, higher layers are more abstract. Each layer's goal subsumes that of the underlying layers, e.g. the decision to move forward by the eat-food layer takes into account the decision of the lowest obstacle-avoidance layer. Behavior need not be planned by a superior layer, rather behaviors may be triggered by sensory inputs and so are only active under circumstances where they might be appropriate. Reinforcement learning has been used to acquire behavior in a hierarchical control system in which each node can learn to improve its behavior with experience. James Albus, while at NIST, developed a theory for intelligent system design named the Reference Model Architecture, a hierarchical control system inspired by RCS.
Albus defines each node to contain these components. Behavior generation is responsible for executing tasks received from the parent node, it plans for, issues tasks to, the subordinate nodes. Sensory perception is responsible for receiving sensations from the subordinate nodes grouping and otherwise processing them into higher level abstractions that update the local state and which form sensations that are sent to the superior node. Value judgment is responsible for evaluating alternative plans. World Model is the local state that provides a model for the controlled system, controlled process, or environment at the abstraction level of the subordinate nodes. At its lowest levels, the RMA can be implemented as a subsumption architecture, in which the world model is mapped directly to the controlled process or real world, avoiding the need for a mathematical abstraction, in which time-constrained reactive planning can be implemented as a finite state machine. Higher levels o