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Lateral computing is a lateral thinking approach to solving computing problems. Lateral thinking has been made popular by Edward de Bono. This thinking technique is applied to generate creative ideas and solve problems. Similarly, by applying lateral-computing techniques to a problem, it can become much easier to arrive at a computationally inexpensive, easy to implement, efficient, innovative or unconventional solution. The traditional or conventional approach to solving computing problems is to either build mathematical models or have an IF- THEN -ELSE structure. For example, a brute-force search is used in many chess engines, but this approach is computationally expensive and sometimes may arrive at poor solutions. It is for problems like this that lateral computing can be useful to form a better solution. A simple problem of truck backup can be used for illustrating lateral-computing. This is one of the difficult tasks for traditional computing techniques, and has been efficiently solved by the use of fuzzy logic (which is a lateral computing technique). Lateral-computing sometimes arrives at a novel solution for particular computing problem by using the model of how living beings, such as how humans, ants, and honeybees, solve a problem; how pure crystals are formed by annealing, or evolution of living beings or quantum mechanics etc. ==Logical thinking and artificial intelligence== Chess position analysis can be used to illustrate the logical thinking. The following board position describes a chess problem which has to be solved with two moves. The white has several options to make a move and checkmate the black. The move Rd5 × Rd7 or Rf7 × Rd7 will immediately provide material advantage to white. There are similar moves which capture pieces and provide immediate material advantages to the white. But a knight move Nc6 which does not provide any material advantage, provides a solution for checkmate for black in two moves. This is an example which illustrates the use of logical thinking. The logical thinking in chess progresses by evaluating the immediate material gain in each move. This will result in a solution which will require more number of moves or failure to checkmate. However, the not so obvious move of knight results in a very powerful checkmate. Even though this move does not look logical, it is the solution to two-move checkmate problem. A computer programmed to play chess might miss out some good opportunities if it does a material-based search to find moves. Several attempts have been made to build the powerful chess computers in history.〔 But these chess computers have been defeated by Grandmaster human chess players. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Lateral computing」の詳細全文を読む スポンサード リンク
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