The problem of programming an artificial ant to follow the Santa Fe trail has been repeatedly used as a benchmark problem. Recently we have shown performance of several techniques is not much better than the best performance obtainable using uniform random search. We suggested that this could be because the program fitness landscape is difficult for hill climbers and the problem is also difficult for Genetic Algorithms as it contains multiple levels of deception. Here we redefine the problem so the ant is obliged to traverse the trail in approximately the correct order. A simple genetic programming system, with no size or depth restriction, is shown to perform approximately three times better with the improved training function
A number of extensions of Ant System, the first ant colony optimization (ACO) algorithm, were pro...
In ant colony optimization (ACO) methods, including Ant System and MAX-MIN Ant System, each ant stoc...
A significant challenge in genetic programming is premature convergence to local optima, which often...
The problem of programming an artificial ant to follow the Santa Fe trail is used as an example prog...
Abstract: Ant programming has been proposed as an alternative to Genetic Programming (GP) for the au...
Natural systems are a source of inspiration for computer algorithms designed to solve optimisation p...
Abstract. Ant Colony Optimization (ACO) has been applied successfully in solving the Traveling Sales...
Ant Colony Optimization (ACO) has been applied successfully in solving the Traveling Salesman Proble...
Ant programming has been proposed as an alternative to Genetic Programming (GP) for the automated pr...
Artificialant problem is considered as a sub-problem of robotic path planning. In this study, it is ...
Ants communicate information by leaving pheromone tracks. A moving ant leaves, in varying quantities...
The evolution of general intelligent behavior continues to be an important goal of genetic programmi...
Marco Dorigo et al. used Ant System (AS) to explore the Symmetric Traveling Salesman Problem and fou...
Different Ants Colony Optimization (ACO) algorithms use pheromone information differently in an atte...
Recently, many methods of evolutionary computation such as Genetic Algorithm (GA) and Genetic Progra...
A number of extensions of Ant System, the first ant colony optimization (ACO) algorithm, were pro...
In ant colony optimization (ACO) methods, including Ant System and MAX-MIN Ant System, each ant stoc...
A significant challenge in genetic programming is premature convergence to local optima, which often...
The problem of programming an artificial ant to follow the Santa Fe trail is used as an example prog...
Abstract: Ant programming has been proposed as an alternative to Genetic Programming (GP) for the au...
Natural systems are a source of inspiration for computer algorithms designed to solve optimisation p...
Abstract. Ant Colony Optimization (ACO) has been applied successfully in solving the Traveling Sales...
Ant Colony Optimization (ACO) has been applied successfully in solving the Traveling Salesman Proble...
Ant programming has been proposed as an alternative to Genetic Programming (GP) for the automated pr...
Artificialant problem is considered as a sub-problem of robotic path planning. In this study, it is ...
Ants communicate information by leaving pheromone tracks. A moving ant leaves, in varying quantities...
The evolution of general intelligent behavior continues to be an important goal of genetic programmi...
Marco Dorigo et al. used Ant System (AS) to explore the Symmetric Traveling Salesman Problem and fou...
Different Ants Colony Optimization (ACO) algorithms use pheromone information differently in an atte...
Recently, many methods of evolutionary computation such as Genetic Algorithm (GA) and Genetic Progra...
A number of extensions of Ant System, the first ant colony optimization (ACO) algorithm, were pro...
In ant colony optimization (ACO) methods, including Ant System and MAX-MIN Ant System, each ant stoc...
A significant challenge in genetic programming is premature convergence to local optima, which often...