The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In recent years, Cartesian Ant Programming (CAP) has been proposed as a swarm-based automatic programming method, which combines graph representations in Cartesian Genetic Programming with search mechanism of Ant Colony Optimization. In CAP, once an ant jumps a number of nodes, the skipped nodes are not utilized and wasted in search. To make the use frequency of nodes uniform, we propose CAP with...
Ant Colony Optimization (ACO) is a swarm-based search method. Multiple ant agents search various solutions and their searches focus on around good solutions by positive feedback mechanism based on pheromone communication. ACO is effective for combinatorial optimization problems. The attempt of applying ACO to automatic programming has been studied in recent years. As one of the attempts, we have previously...
Ant Programming (AP) is an automatic programming method, which combines tree-structural representations of Genetic Programming (GP) and search mechanism by pheromone communications of ants in Ant Colony Optimization (ACO). In AP, a single prototype tree, in which respective nodes have different pheromone tables, is prepared, and an ant searches solutions under the prototype tree. The structure of...
Genetic Programming (GP) and Simulated Annealing Programming (SAP) are typical metaheuristic methods for automatic programming. We propose a new method, Parallel — Genetic and Annealing Programming (P-GAP) which combines GP and SAP. In P-GAP, multiple initial populations are generated by SAP. Respective populations evolve by parallel GP. As the generation proceeds, populations are integrated gradually...
Genetic Programming (GP) is well-known as an evolutionary method for automatic programming. GP can optimize tree-structural programs. Cartesian GP (CGP) is one of the extensions of GP, which generates the graph structural programs. By using the graph structure, the solutions can be represented by more compact programs. Therefore, CGP is widely applied to the various problems. As a different approach...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.