Backtracking is a general algorithm for finding all or some solutions to some computational problem , that incrementally ... state.edu gurari course cis680 cis680Ch19.html QQ1 51 128 Backtracking algorithms title CIS 680 DATA STRUCTURES Chapter 19 Backtracking Algorithms year 1999 author Gurari, Eitan ref The classic textbook example of the use of backtracking is the eight queens puzzle , that asks for all arrangements of eight queens on a standard chess board so that no queen attacks any other. In the common backtracking ... can be abandoned, since it cannot possibly be completed to a valid solution. Backtracking can be applied ... a given value in an unordered table. When it is applicable, however, backtracking is often ... eliminate a large number of candidates with a single test. Backtracking is an important tool for solving ... programming language Icon , Planner programming language Planner and Prolog . Backtracking is also utilized in the diff difference engine for the MediaWiki software. Backtracking depends on user ... in general backtracking facility. Description of the method The backtracking algorithm enumerates ... further. The backtracking algorithm traverses this search tree recursion computer science recursively ... In order to apply backtracking to a specific class of problems, one must provide the data P ... s . output P , c use the solution c of P , as appropriate to the application. The backtracking ... false for every ancestor t of c in the search tree. On the other hand, the efficiency of the backtracking ... to yield other valid solutions. The first and next procedures are used by the backtracking algorithm ... language Planner and Prolog , which use backtracking internally to generate answers. Backtracking ... backtracking solution to this problem, one could define a partial candidate as a list of integers ... F cannot be satisfied by any list of n integers that begins with the k elements of c . For backtracking ... . In addition to retaining minimal recovery values used in backing up, backtracking implementations ... more details
In unconstrained optimization mathematics optimization , the backtracking linesearch strategy is used as part of a line search method, to compute how far one should move along a given search direction. Motivation Usually it is undesirable to exactly minimize the function math displaystyle phi alpha math in the generic linesearch algorithm. One way to inexactly minimize math displaystyle phi math is by finding an math displaystyle alpha k math that gives a sufficient decrease in the objective function math f mathbb R n to mathbb R math assumed smooth function smooth , in the sense of the Wolfe conditions Armijo Goldstein condition holding. This condition, when used appropriately as part of a backtracking linesearch, is enough to generate an acceptable step length. It is not sufficient on its own to ensure that a reasonable value is generated, since all math displaystyle alpha math small enough will satisfy the Armijo condition. To avoid the selection of steps that are too short, the additional Wolfe conditions curvature condition is usually imposed. Algorithm i Set iteration counter math scriptstyle j , ,0 math . Make an initial guess math scriptstyle alpha 0 , ,0 math and choose some math scriptstyle tau , in , 0,1 . , math ii Until math scriptstyle alpha j , math satisfies the Wolfe conditions Armijo Goldstein condition math alpha j 1 tau alpha j, , math math j j 1. , math iii Return math scriptstyle alpha alpha j. , math In other words, reduce math scriptstyle alpha 0 math geometrically, with rate math scriptstyle tau , math , until the Armijo Goldstein condition holds. See also Line search References cite book first1 J. E. last1 Dennis first2 R. B. last2 Schnabel title Numerical Methods for Unconstrained Optimization and Nonlinear Equations publisher SIAM Publications location Philadelphia year 1996 cite book first1 J. last1 Nocedal first2 S. J. last2 Wright title Numerical optimization publisher Springer Verlag location New York, NY year 1999 Category Mathematical ... more details
In backtracking algorithm s, look ahead is the generic term for a Subroutine subprocedure that attempts to foresee the effects of choosing a branch computer science branching Variable programming variable to evaluate or one of its values. The two main aims of look ahead are to choose a variable to evaluate next and the order of values to assign to it. Constraint satisfaction In a general constraint satisfaction problem , every variable can take a value in a domain. A backtracking algorithm therefore iteratively chooses a variable and tests each of its possible values for each value the algorithm is recursion recursively run. Look ahead is used to check the effects of choosing a given variable to evaluate or to decide the order of values to give to it. Look ahead techniques Image Forward arc 0.svg thumb left 200px In this example, x sub 1 sub 2 and the tentative assignment x sub 2 sub 1 is considered. Image Forward arc 1.svg thumb 200px Forward checking only checks whether each of the unassigned variables x sub 3 sub and x sub 4 sub is consistent with the partial assignment, removing the value 2 from their domains. The simpler technique for evaluating the effect of a specific assignment to a variable is called forward checking . Given the current partial solution and a candidate assignment to evaluate, it checks whether another variable can take a consistent value. In other words, it first extends the current partial solution with the tentative value for the considered variable it then considers every other variable math x k math that is still unassigned, and checks whether there exists an evaluation of math x k math that is consistent with the extended partial solution. More generally, forward checking determines the values for math x k math that are consistent with the extended assignment. Image Forward arc 2.svg thumb 200px Arc consistency look ahead also checks whether the values of x sub 3 sub and x sub 4 sub are consistent with each other red lines removing also ... more details
Beam Stack Search ref Zhou, Rong. Hansen, Eric. http citeseerx.ist.psu.edu viewdoc download?doi 10.1.1.71.4147&rep rep1&type pdf Beam Stack Search Integrating Backtracking with Beam Search . 2005. ref is a search algorithm that combines chronological backtracking that is, depth first search with beam search and is similar to Depth First Beam Search ref name furcy Furcy, David. Koenig, Sven. Limited Discrepancy Beam Search . 2005. http www.ijcai.org papers 0596.pdf ref . Both search algorithms are anytime algorithm s that find good but likely sub optimal solutions quickly, like beam search, then backtrack and continue to find improved solutions until convergence to an optimal solution. Implementation Beam Stack Search uses the beam stack as a data structure to integrate chronological backtracking with beam search and can be combined with the divide and conquer algorithm technique, resulting in divide and conquer beam stack search. Alternatives Beam Search Using Limited Discrepancy Backtracking ref name furcy BULB is a search algorithm that combines limited discrepancy search with beam search and thus performs non chronological backtracking , which often outperforms the chronological backtracking done by Beam Stack Search and Depth First Beam Search. References reflist DEFAULTSORT Beam Stack Search Category Search algorithms algorithm stub th ... more details
Backtaxi also known as backtrack is an airport ground procedure which involves the use of any portion of a runway as a taxiway for an aircraft to taxiing taxi in the opposite direction from which it will take off or has landed. The procedure is commonly used at smaller airports and private strips which may not have separate paved taxiways parallel to the runway. At controlled airports, take off or landing clearances do not authorize the pilot to reverse course and backtrack along the runway, unless specified by air traffic control ref Aeronautical Information Publication Australia ENR 1.1 5.2 ref ref Aeronautical Information Publication Australia ENR 1.1 16.2 ref . At uncontrolled airports, pilots are recommended to broadcast their intentions while backtracking in the interest of safety, for example Entering and backtracking runway 36 would indicate the aircraft is taxiing along a magnetic heading of 180 degrees, against the flow of traffic. An infamous and rare example of where backtracking was used for large commercial aircraft was the Tenerife airport disaster , where two Boeing 747 s at Tenerife North Airport were required to backtaxi in order to position themselves for take off. The ramps and taxiways were occupied by numerous parked aircraft which had been detoured as a result of a bomb threat at another airport. Notes references Category Aircraft operations Aviation stub ... more details
Multiple issues unreferenced September 2008 context August 2009 Programming paradigms A nondeterministic programming language is a programming language language which can specify, at certain points in the program called choice points , various alternatives for Control flow program flow . Unlike an Conditional programming if then statement , the method of choice between these alternatives is not directly specified by the programmer the program must decide at run time program lifecycle phase run time between the alternatives, via some general method applied to all choice points. A programmer specifies a limited number of alternatives, but the program must later choose between them. Choose is, in fact, a typical name for the nondeterministic operator. A hierarchy of choice points may be formed, with higher level choices leading to branches that contain lower level choices within them. One method of choice is embodied in backtracking systems such as http mitpress.mit.edu sicp full text sicp book node91.html AMB , or unification in Prolog , in which some alternatives may fail, causing the program to backtrack and try other alternatives. If all alternatives fail at a particular choice point, then an entire branch fails, and the program will backtrack further, to an older choice point. One complication is that, because any choice is tentative and may be remade, the system must be able to restore old program states by undoing side effects caused by partially executing a branch that eventually failed. Another method of choice is reinforcement learning, embodied in systems such as http www.cs.berkeley.edu russell papers aaai02 alisp.pdf Alisp . In such systems, rather than backtracking, the system keeps track of some measure of success and learns which choices often lead to success, and in which situations both internal program state and environmental input may affect the choice . These systems are suitable for applications to robotics and other domains in which backtracking ... more details
todo add indices and citations doublecheck backtracking doublecheck continuations macros hygienic or not? new entry LISP70 which redirects to here MLisp is also another name for Mocklisp , a stripped down version of Lisp used as an extension language in Gosling Emacs . MLISP is a variant of Lisp programming language Lisp with an ALGOL Algol like syntax based on M expression M Expressions , which were the function syntax in the original description of Lisp by John McCarthy computer scientist John McCarthy . McCarthy s M expressions were never implemented. MLISP was first implemented for the IBM 360 by Horace Enea and then reimplemented for the PDP 10 by David Canfield Smith. This second implementation also supported a special kind of lambdas Fexpr FEXPR , which do not evaluate their arguments Could this be used to implement lazy evaluation? . As in Lisp programming language Lisp 1 or Scheme programming language Scheme , there was a single namespace for variables and functions. While MLISP was just a preprocessor with an alternative, more reader friendly syntax for Lisp, the descendant MLISP 2 introduced new concepts interactive interpretation of programs instead of compilation extensibility with a syntax description language see hygienic macro s pattern matching backtracking by the use of Closure computer science closure s on a stack and indices for continuation s MLISP2 was called a transitional language by the authors. Larry Tesler improved the pattern matching system to implement a successor language called LISP70 , which was only completed to a preliminary version. Though this path of LISP evolution is widely neglected, it resembles some features, later found in ML programming language ML or Scheme programming language Scheme . M LISP is a second branch &mdash independent ... report Smith, David Canfield and Enea, Horace J. 1973 Backtracking in MLISP2 an efficient backtracking method for LISP http dli.iiit.ac.in ijcai IJCAI 73 PDF 074.pdf 074.pdf Tesler, Lawrence ... more details
A lean theorem prover is an Automated theorem proving automated theorem prover implemented in a minimum amount of code. Lean provers are generally fact date December 2007 implemented in Prolog , and make proficient use of the backtracking engine and Logic programming logic variables of that language. Lean provers can be as small as a few hundred bytes of source code . Lean theorem provers http www.leancop.de leanCoP , a prover for classical first order logic in 333 byte s http i12www.ira.uka.de leantap leanTAP science software stub Category Theorem proving software systems ... more details
Wiktionarypar Backtrack Backtrack may refer to Back Track , a first person shooter for the Game Boy Advance BackTrack , a Linux distribution BackTrack magazine BackTrack magazine , a British railway history monthly magazine Backtrack 1990 film Backtrack 1990 film , alternative name to Catchfire , a 1990 drama film Backtrack Transformers , a fictional character in the Transformers series Backtrack western novel Backtrack western novel , a 1965 western novel written by Milton Lott Backtracking , a search algorithm in computing Backtracks AC DC album Backtracks AC DC album , an album by AC DC Backtracks Poco album Backtracks Poco album , an album by Poco Disambig de Backtrack ko ... more details
In constraint satisfaction problem constraint satisfaction backtracking algorithm s, constraint learning is a technique for improving efficiency. It works by recording new constraints whenever an inconsistency is found. This new constraint may reduce the search space , as future partial evaluations may be found inconsistent without further search. Clause learning is the name of this technique when applied to propositional satisfiability . Definition Backtracking algorithms work by choosing an unassigned variable and recursively solve the problems obtained by assigning a value to this variable. Whenever the current partial solution is found inconsistent, the algorithm goes back to the previously assigned variable, as expected by recursion. A constraint learning algorithm differs because it tries to record some information, before backtracking, in form of a new constraint. This can reduce the further search because the subsequent search may encounter another partial solution that is inconsistent with this new constraint. If the algorithm has learned the new constraint, it will backtrack from this solution, while the original backtracking algorithm would do a subsequent search. If the partial solution math x 1 a 1, ldots,x k a k math is inconsistent, the problem instance implies the constraint stating that math x i a i math cannot be true for all math i in 1,k math at the same time. However, recording this constraint is not useful, as this partial solution will not be encountered again due to the way backtracking proceed. On the other hand, if a subset of this evaluation is inconsistent, the corresponding constraint may be useful in the subsequent search, as the same subset of the partial evaluation may occur again in the search. For example, the algorithm may encounter an evaluation ... two factors. On one hand, the more often a recorded constraint is violated, the more often backtracking ... also Look ahead backtracking Backjumping References cite book first Rina last Dechter title Constraint ... more details
In constraint satisfaction , backmarking is a variant of the backtracking algorithm. Backmarking works like backtracking by iteratively evaluating variables in a given order, for example, math x 1, ldots,x n math . It improves over backtracking by maintaining information about the last time a variable math x i math was instantiated to a value and information about what changed since then. In particular Image Backmarking 1.png thumb 180px An example, in which search has reached xi d the first time. for each variable math x i math and value math a math , the algorithm records information about the last time math x i math has been set to math a math in particular, it stores the minimal index math j i math such that the assignment to math x 1, ldots,x j,x i math was then inconsistent for each variable math x i math , the algorithm stores some information relative to what changed since the last time it has evaluated math x i math in particular, it stores the minimal index math k i math of a variable that was changed since then. The first information is collected and stored every time the algorithm evaluates a variable math x i math to math a math , and is done by simply checking consistency of the current assignments for math x 1,x i math , for math x 1,x 2,x i math , for math x 1,x 2,x 3,x i math , etc. Image Backmarking 2.png thumb 180px When search reaches xi d for the second time, part of the path is the same as the first time. The second information is changed every time another variable is evaluated. In particular, the index of the maximal unchanged variable since the last evaluation of math x i math is possibly changed every time another variable math x j math changes value. Every time an arbitrary variable math x j math changes, all variables math x i math with math i ..., whenever backtracking would set math x i a math , backmarking compares the two indexes ... variants to backtracking, backmarking does not reduce the search space but only possibly reduce the number ... more details
Image Acp tzero DSC00467.jpg thumb AC Propulsion ACP Backtracking Genset trailer A genset trailer is a range extending device for use with battery electric vehicle s consisting of an internal combustion engine and an electrical generator collectively called a engine generator genset . They run on traditional fuels such as gasoline or diesel and are sized to provide the continuous power requirements for the vehicle they are used with. Most small to midsized passenger vehicles would require 15 to 20 kW for unlimited freeway travel using fuel. Larger vehicles could require 30 kW or more of power depending on how heavy or un aerodynamic they happen to be. One such trailer is the AC Propulsion backtracking Long Ranger range extending gas fueled trailer, making it a gas electric series plug in hybrid electric vehicle . This trailer used a 500 cc Kawasaki engine with a 9.5 gallons 40 liter fuel tank and achieved 30 to 35 mpg 6.72 to 7.84 litres 100 km . It is rated at 20 kW DC output and can maintain 60 to 80 mph 95 to 128 km h . The setbacks involved with this system are emissions from running the engine carbon dioxide CO sub 2 sub and other gases , as well as the additional cost of gasoline. Another setback with this system is the fact that it has to be a trailer, as these are impractical for some drivers. See also Plug in hybrid Pusher trailer External links http www.austinev.org evalbum pushers.html pusher example http www.acpropulsion.com reports Low Emiss Range Ext.pdf http evnut.com rav longranger.htm Experimental model, also by ACPropulsion, for the Toyota RAV4 EV Category Electric vehicles Category Trailers Category Plug in hybrid vehicles automotive tech stub ... more details
In backtracking algorithm s, backjumping is a technique that reduces search space , therefore increasing efficiency. While backtracking always goes up one level in the search tree when all values for a variable have been tested, backjumping may go up more levels. In this article, a fixed order of evaluation of variables math x 1, ldots,x n math is used, but the same considerations apply to a dynamic order of evaluation. gallery Image Backtracking no backjumping.svg A search tree visited by regular backtracking Image Backtracking with backjumping.svg A backjump the grey node is not visited gallery Definition Whenever backtracking has tried all values for a variable without finding any solution, it reconsiders the last of the previously assigned variables, changing its value or further backtracking if no other values are to be tried. If math x 1 a 1, ldots,x k a k math is the current partial assignment and all values for math x k 1 math have been tried without finding a solution, backtracking concludes that no solution extending math x 1 a 1, ldots,x k a k math exists. It then goes up to math x k math , changing its value if possible, backtracking again otherwise. The partial assignment is not always necessary in full to prove that no value of math x k 1 math lead to a solution. In particular ... x 1x 2x 3x 4 math has been unsuccessfully tried with every possible value of math x 5 math . Backtracking goes back to math x 4 math , trying to assign it a new value. Instead of backtracking, the algorithm ... only in leaf dead ends. In other words, it works differently to backtracking only when every possible ... the variable of the node and collected in the set of the destination of backtracking or backjumping ... set. When further backtracking or backjumping from the node, the variable of the node is removed from this set, and the set is sent to the node that is the destination of backtracking or backjumping ... the variable of the node and collected into the destination of backtracking or backjumping. Conflict ... more details
In natural language processing , deterministic parsing refers to parsing algorithm s that do not Backtracking back up . LR parser LR parsers are an example. This meaning of the words deterministic and non deterministic differs from that used to describe nondeterministic algorithm s. The deterministic behavior is desired and expected in Compiler compiling programming language s. In natural language processing, it was thought for a long time that deterministic parsing is impossible due to ambiguity inherent in natural languages many sentences have more than one plausible parse . Thus, non deterministic approaches such as the chart parser had to be applied. However, Mitch Marcus proposed in 1978 the Parsifal parser that was able to deal with ambiguities while still keeping the deterministic behavior. See also Deterministic context free grammar References Alfred V. Aho , Stephen C. Johnson , Jeffrey D. Ullman 1975 Deterministic parsing of ambiguous grammars. Comm. ACM 18 8 441 452. Mitchell Marcus 1978 A Theory of Syntactic Recognition for Natural Language. PhD Thesis, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology. Comp sci stub Category Parsing ... more details
For the novel by James Dashner The Maze Runner Refimprove date December 2006 Maze runner is a Computer network connection routing method that represents the entire routing space as a grid. Parts of this grid are blocked by components, specialised areas, or already present wiring . The grid size corresponds to the wiring pitch of the area. The goal is to find a chain of grid cells that go from point A to point B. A maze runner may use the Lee algorithm . It uses a wave propagation style a wave are all cells that can be reached in n steps throughout the routing space. The wave stops when the target is reached, and the path determined by backtracking through the cells. References Citation last Lee first C. Y. title An Algorithm for Path Connections and Its Applications journal IRE Transactions on Electronic Computers volume EC 10 issue 2 pages 346&ndash 365 year 1961 issn doi . One of the first descriptions of a maze router. Category Electronic engineering Category Electronic design automation Category Electronics optimization electronics stub ... more details
Best bin first is a search algorithm that is designed to efficiently find an approximate solution to the nearest neighbor search problem in very high dimensional spaces. The algorithm is based on a variant of the kd tree search algorithm which makes indexing higher dimensional spaces possible. Best bin first is an approximate algorithm which returns the nearest neighbor for a large fraction of queries and a very close neighbor otherwise. ref Beis, J. and Lowe, D. G. 1997. http citeseerx.ist.psu.edu viewdoc download?doi 10.1.1.23.9493&rep rep1&type pdf Shape indexing using approximate nearest neighbour search in high dimensional spaces . Conference on Computer Vision and Pattern Recognition, Puerto Rico, pp. 1000 1006. ref Difference from kd tree Backtracking is according to a priority queue based on closeness. Search a fixed number of nearest candidates and stop. A speedup of two orders of magnitude is typical. References Reflist Category Search algorithms algorithm stub th ... more details
technical date March 2012 unreferenced date March 2012 Left factoring is the action taken when a grammar leads backtracking while making parsing syntax tree. Lets take an example Let we have a grammar A bcW bcE W x E q Now lets have a look on the production A bcW bcE , here bc is repeating. If we want to parse a string bcq , then firstly we have two choices..either choose A bcW or A bcE.both have same probability.Let randomly we choose A bcW. Then when we are over with bc and turn to parse q ,then we have to backtrack because this production is in A bcE so this shows the problem with such type of problem. Now to overcome this problem we have a concept of Left factoring. In this we take common symbols in a new non terminal. Lets have a look on how we can do it. Above grammar after applying left factoring is A bcX X W E W x E q That s it. Uncategorized date April 2012 ... more details
attempts at integration of declarative programming constructs such as automatic backtracking into imperative ... of choice points and backtracking a code FORALL code statement that introduces a controlled form of iteration over the backtracking unification computing unification which, although limited to the use ... Programming Language With Backtracking . Jacob Brunekreef 1998 . http www.science.uva.nl pub programming ... more details
The Davis Putnam Logemann Loveland DPLL algorithm is a complete, backtracking based search algorithm for Boolean satisfiability problem deciding the satisfiability of propositional logic propositional logic formulae in conjunctive normal form , i.e. for solving the Boolean satisfiability problem CNF SAT problem. It was introduced in 1962 by Martin Davis , Hilary Putnam , George Logemann and Donald W. Loveland and is a refinement of the earlier Davis Putnam algorithm , which is a Resolution logic resolution based procedure developed by Davis and Putnam in 1960. Especially in older publications, the Davis Logemann Loveland algorithm is often referred to as the Davis Putnam method or the DP algorithm . Other common names that maintain the distinction are DLL and DPLL. DPLL is a highly efficient procedure and after almost 50 years still forms the basis for most efficient complete SAT solvers, as well as for many automated theorem proving theorem provers for fragments of first order logic . ref Citation title Abstract DPLL and Abstract DPLL Modulo Theories first1 Robert last1 Nieuwenhuis first2 Albert last2 Oliveras first3 Cesar last3 Tinelly year 2004 pages 36 50 journal Logic for Programming ... papers lpar04.pdf urltype pdf ref Infobox algorithm name DPLL image image Backtracking no backjumping.svg ... The basic backtracking algorithm runs by choosing a literal, assigning a truth value to it, simplifying ... algorithm enhances over the backtracking algorithm by the eager use of the following rules at each ... is the literal considered in the backtracking step. As a result, this is not exactly an algorithm ... faster, especially the part on unit propagation and defining variants of the basic backtracking algorithm. The latter direction include non chronological backtracking aka. backjumping and Clause logic clause learning . These refinements describe a method of backtracking after reaching a conflict ... Backtracking search algorithms ref See also Davis Putnam algorithm Chaff algorithm Proof complexity ... more details
Orphan date February 2009 The Market of Alturien is a board game for 2 to 6 players, released in 2007. Players assume the roles of stall traders in a market town , competing to attract customer s. The board is divided into squares, with most squares permitting the building of a stall, always by at most one player. Six Customer models of varying wealth are moved about the board no backtracking, although they may walk in circles by the players according to the rolls of the dice , and spend their money at the stall at which they arrive. After at least one player has reached a predetermined amount of wealth, a Thief is released from the docks and may also be moved by the players stealing from whosever stall he arrives in front of. If a player does not like the result they roll at the start of their turn, then they may move the Thief and then roll again, although they may not repeat this procedure a second time. Also once per turn, a player may buy either an additional market stall , an extension to one of their preexisting stalls that sells more goods when a customer arrives at it , an investment from a set of four that offer various special rules, such as being able to roll two dice and pick the most satisfactory result , or a prestige card , which determine the winner of the game. External links bgg 27800 DEFAULTSORT Market of Alturien Category Economic simulation board games board game stub ... more details
of Search algorithm search . The most used techniques are variants of backtracking, constraint propagation, and local search. Backtracking is a recursive algorithm. It maintains a partial assignment .... When all values have been tried, the algorithm backtracks. In this basic backtracking algorithm ... variants of backtracking exists. Backmarking improves the efficiency of checking consistency. Backjumping allows saving part of the search by backtracking more than one variable in some cases. Constraint .... Look ahead backtracking Look ahead is also often used in backtracking to attempt to foresee the effects ... more details
matrix has no columns, then they have all been filled and the selected rows form the solution. Backtracking ... requirement of using that algorithm is that backtracking must be done as an exact reversal of eliminations ... more details
Refimprove date December 2009 In computer science , a chart parser is a type of parsing parser suitable for ambiguous grammars including grammars of natural language s . It uses the dynamic programming approach partial hypothesized results are stored in a structure called a chart data structure chart and can be re used. This eliminates backtracking and prevents a combinatorial explosion . Chart parsing was developed by Martin Kay . ref cite web url http webdocs.cs.ualberta.ca lindek 650 papers chartParsing.pdf title Chart Parsing accessdate 20 November 2011 ref Types of chart parsers A common approach is to use a variant of the Viterbi algorithm . The Earley parser is a type of chart parser mainly used for parsing in computational linguistics , named for its inventor. Another chart parsing algorithm is the Cocke Younger Kasami algorithm Cocke Younger Kasami CYK algorithm. Chart parsers can also be used for parsing computer languages. Earley parsers in particular have been used in compiler compiler s where their ability to parse using arbitrary Context free grammars eases the task of writing the grammar for a particular language. However their lower efficiency has led to people avoiding them for most compiler work. In bidirectional chart parsing , edges of the chart are marked with a direction, either forwards or backwards, and rules are enforced on the direction in which edges must point in order to be combined into further edges. In incremental chart parsing , the chart is constructed incrementally as the text is edited by the user, with each change to the text resulting in the minimal possible corresponding change to the chart. We can distinguish Top down parsing top down and bottom up parser bottom up chart parsers, and active chart parser active and passive chart parser passive chart parsers. Parsing ambiguity in natural languages The most serious problem faced by parsers is the ambiguity of natural languages. See also Brute force search Dynamic programming Refe ... more details
SAIL , the Stanford Artificial Intelligence Language , was developed by Dan Swinehart and Bob Sproull of the Stanford AI Lab in 1970. It was originally a large ALGOL 60 like language for the PDP 10 and DECSYSTEM 20 . SAIL s main feature is a symbolic data system based upon an associative store based on the LEAP programming language LEAP system of Jerry Feldman and Paul Rovner . Items may be stored as unordered sets or as associations triples . Other features include processes, events and interrupts, contexts, backtracking and record garbage collection. It also has block structured macros, a coroutining facility and some new data types intended for building search trees and association lists. A number of interesting software systems were coded in SAIL, including some early versions of File Transfer Protocol FTP and TeX , a document formatting system called PUB, and the first general purpose, interactive spreadsheet program called BRIGHT. In 1978, there were half a dozen different operating systems for the PDP 10 Incompatible Timesharing System ITS MIT , WAITS Stanford , TOPS 10 DEC , CMU TOPS 10 Carnegie Mellon , TENEX Bolt, Beranek and Newman BBN , and TOPS 20 DEC, based on TENEX . SAIL was ported from WAITS to ITS so that MIT researchers could make use of software developed at Stanford University . Every port usually required the rewriting of I O code in each application. A machine independent version of SAIL called MAINSAIL was developed in the late 1970s and was used to develop many eCAD design tools during the 1980s. MAINSAIL was easily portable to new processors and operating systems, and is still in limited use as of 2005 lc on . External links http www.xidak.com mainsail documentation set 1630 html docset MLANM.html Documentation for MAINSAIL. http pdp 10.trailing edge.com decuslib20 01 01 decus 20 0002 sail.tut.html A SAIL Tutorial from the DECUS PDP 10 library tapes FOLDOC Category Algol programming language family compu lang stub ar de SAIL P ... more details
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