3 Ant Related Studies

The Artificial Ant problem was investigated in numerous studies. Langdon and Poli (2002) examined several aspects of the search space for the Ant problem. The authors measure the search effort required for genetic programming, several variations of genetic programming, several random search techniques and several stochastic search methods. While genetic programming performed at least as good as the random search methods, some versions of stochastic hill-climbing, including population based hill-climbing, performed equally well or better than genetic programming. Langdon and Poli noted that the Ant problem is highly deceptive. That is, there are many possible solutions that are symmetrical, and because there is no requirement that a particular path is followed, solutions with equal fitness can take very different approaches to solving the problem. Langdon and Poli later showed that by encouraging the population to follow similar paths, the problem became considerably easier for genetic programming.