Dijkstra’s Algorithm
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Dijkstra’s Algorithm
Dijkstra's algorithm ( ) is an algorithm for finding the shortest paths between nodes in a weighted graph, which may represent, for example, a road network. It was conceived by computer scientist Edsger W. Dijkstra in 1956 and published three years later. Dijkstra's algorithm finds the shortest path from a given source node to every other node. It can be used to find the shortest path to a specific destination node, by terminating the algorithm after determining the shortest path to the destination node. For example, if the nodes of the graph represent cities, and the costs of edges represent the distances between pairs of cities connected by a direct road, then Dijkstra's algorithm can be used to find the shortest route between one city and all other cities. A common application of shortest path algorithms is network routing protocols, most notably IS-IS (Intermediate System to Intermediate System) and OSPF (Open Shortest Path First). It is also employed as a subroutine in a ...
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Search Algorithm
In computer science, a search algorithm is an algorithm designed to solve a search problem. Search algorithms work to retrieve information stored within particular data structure, or calculated in the Feasible region, search space of a problem domain, with Continuous or discrete variable, either discrete or continuous values. Although Search engine (computing), search engines use search algorithms, they belong to the study of information retrieval, not algorithmics. The appropriate search algorithm to use often depends on the data structure being searched, and may also include prior knowledge about the data. Search algorithms can be made faster or more efficient by specially constructed database structures, such as search trees, hash maps, and database indexes. Search algorithms can be classified based on their mechanism of searching into three types of algorithms: linear, binary, and hashing. Linear search algorithms check every record for the one associated with a target key i ...
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Subroutine
In computer programming, a function (also procedure, method, subroutine, routine, or subprogram) is a callable unit of software logic that has a well-defined interface and behavior and can be invoked multiple times. Callable units provide a powerful programming tool. The primary purpose is to allow for the decomposition of a large and/or complicated problem into chunks that have relatively low cognitive load and to assign the chunks meaningful names (unless they are anonymous). Judicious application can reduce the cost of developing and maintaining software, while increasing its quality and reliability. Callable units are present at multiple levels of abstraction in the programming environment. For example, a programmer may write a function in source code that is compiled to machine code that implements similar semantics. There is a callable unit in the source code and an associated one in the machine code, but they are different kinds of callable units with different impl ...
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Rotterdam
Rotterdam ( , ; ; ) is the second-largest List of cities in the Netherlands by province, city in the Netherlands after the national capital of Amsterdam. It is in the Provinces of the Netherlands, province of South Holland, part of the North Sea mouth of the Rhine–Meuse–Scheldt delta, via the Nieuwe Maas, New Meuse inland shipping channel, dug to connect to the Meuse at first and now to the Rhine. Rotterdam's history goes back to 1270, when a dam was constructed in the Rotte (river), Rotte. In 1340, Rotterdam was granted city rights by William II, Count of Hainaut, William IV, Count of Holland. The Rotterdam–The Hague metropolitan area, with a population of approximately 2.7 million, is the List of urban areas in the European Union, 10th-largest in the European Union and the most populous in the country. A major logistic and economic centre, Rotterdam is Port of Rotterdam, Europe's largest seaport. In 2022, Rotterdam had a population of 655,468 and is home to over 1 ...
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Best-first Search
Best-first search is a class of search algorithms which explores a graph by expanding the most promising node chosen according to a specified rule. Judea Pearl described best-first search as estimating the promise of node ''n'' by a "heuristic evaluation function f(n) which, in general, may depend on the description of ''n'', the description of the goal, the information gathered by the search up to that point, and most importantly, on any extra knowledge about the problem domain." Some authors have used "best-first search" to refer specifically to a search with a heuristic that attempts to predict how close the end of a path is to a solution (or, goal), so that paths which are judged to be closer to a solution (or, goal) are expanded first. This specific type of search is called '' greedy best-first search'' or ''pure heuristic search''. Efficient selection of the current best candidate for extension is typically implemented using a priority queue. The A* search algorithm is a ...
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Artificial Intelligence
Artificial intelligence (AI) is the capability of computer, computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of research in computer science that develops and studies methods and software that enable machines to machine perception, perceive their environment and use machine learning, learning and intelligence to take actions that maximize their chances of achieving defined goals. High-profile applications of AI include advanced web search engines (e.g., Google Search); recommendation systems (used by YouTube, Amazon (company), Amazon, and Netflix); virtual assistants (e.g., Google Assistant, Siri, and Amazon Alexa, Alexa); autonomous vehicles (e.g., Waymo); Generative artificial intelligence, generative and Computational creativity, creative tools (e.g., ChatGPT and AI art); and Superintelligence, superhuman play and analysis in strategy games (e.g., ...
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Monotonic Function
In mathematics, a monotonic function (or monotone function) is a function between ordered sets that preserves or reverses the given order. This concept first arose in calculus, and was later generalized to the more abstract setting of order theory. In calculus and analysis In calculus, a function f defined on a subset of the real numbers with real values is called ''monotonic'' if it is either entirely non-decreasing, or entirely non-increasing. That is, as per Fig. 1, a function that increases monotonically does not exclusively have to increase, it simply must not decrease. A function is termed ''monotonically increasing'' (also ''increasing'' or ''non-decreasing'') if for all x and y such that x \leq y one has f\!\left(x\right) \leq f\!\left(y\right), so f preserves the order (see Figure 1). Likewise, a function is called ''monotonically decreasing'' (also ''decreasing'' or ''non-increasing'') if, whenever x \leq y, then f\!\left(x\right) \geq f\!\left(y\right), ...
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Partially Ordered Set
In mathematics, especially order theory, a partial order on a Set (mathematics), set is an arrangement such that, for certain pairs of elements, one precedes the other. The word ''partial'' is used to indicate that not every pair of elements needs to be comparable; that is, there may be pairs for which neither element precedes the other. Partial orders thus generalize total orders, in which every pair is comparable. Formally, a partial order is a homogeneous binary relation that is Reflexive relation, reflexive, antisymmetric relation, antisymmetric, and Transitive relation, transitive. A partially ordered set (poset for short) is an ordered pair P=(X,\leq) consisting of a set X (called the ''ground set'' of P) and a partial order \leq on X. When the meaning is clear from context and there is no ambiguity about the partial order, the set X itself is sometimes called a poset. Partial order relations The term ''partial order'' usually refers to the reflexive partial order relatio ...
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Contraction Hierarchy
In computer science, the method of contraction hierarchies is a Speedup, speed-up technique for finding the Shortest path problem, shortest path in a Graph theory, graph. The most intuitive applications are car-navigation systems: a user wants to drive from A to B using the quickest possible route. The metric optimized here is the travel time. Intersections are represented by Vertex (graph theory), vertices, the road sections connecting them by Edge (graph theory), edges. The edge weights represent the time it takes to drive along this segment of the road. A path from A to B is a sequence of edges (road sections); the shortest path is the one with the minimal sum of edge weights among all possible paths. The shortest path in a graph can be computed using Dijkstra's algorithm but, given that road networks consist of tens of millions of vertices, this is impractical. Contraction hierarchies is a speed-up method optimized to exploit properties of graphs representing road networks. The s ...
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