a study on artificial intelligence planning
... beyond the traditional AI toolbox. The realistic planning in dynamic situations try to observe and interpret planning activities here. The more realistic model is interleaved planning and execution. This covers plan superposition, plan revision and re-planning. Dynamic planning is a closed loop betw ...
... beyond the traditional AI toolbox. The realistic planning in dynamic situations try to observe and interpret planning activities here. The more realistic model is interleaved planning and execution. This covers plan superposition, plan revision and re-planning. Dynamic planning is a closed loop betw ...
Artificial Intelligence
... making.The phrase “AI” thus can be defined as the simulation of human intelligence on a machine, so as to make the machine efficient to identify and use the righ piece of “Knowledge” at a given step of solving a problem. A system capable of planning and executing the right task at the right time is ...
... making.The phrase “AI” thus can be defined as the simulation of human intelligence on a machine, so as to make the machine efficient to identify and use the righ piece of “Knowledge” at a given step of solving a problem. A system capable of planning and executing the right task at the right time is ...
A Comparative Analysis of Association Rules Mining Algorithms
... ssociation rule mining is to find out association rules that satisfy the predefined minimum support and confidence from a given database. The problem is usually decomposed into two sub problems. One is to find those itemsets whose occurrences exceed a predefined threshold in the database; those item ...
... ssociation rule mining is to find out association rules that satisfy the predefined minimum support and confidence from a given database. The problem is usually decomposed into two sub problems. One is to find those itemsets whose occurrences exceed a predefined threshold in the database; those item ...
Genetic algorithm
In the field of artificial intelligence, a genetic algorithm (GA) is a search heuristic that mimics the process of natural selection. This heuristic (also sometimes called a metaheuristic) is routinely used to generate useful solutions to optimization and search problems. Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover.