A Simulated Motion Planning Algorithm in 2d And 3d Environments Using Hill Climbing
نویسندگان
چکیده
منابع مشابه
When a genetic algorithm outperforms hill-climbing
A toy optimisation problem is introduced which consists of a ÿtness gradient broken up by a series of hurdles. The performance of a hill-climber and a stochastic hill-climber are computed. These are compared with the empirically observed performance of a genetic algorithm (GA) with and without. The hill-climber with a suuciently large neighbourhood outperforms the stochastic hill-climber, but i...
متن کاملPALO: A Probabilistic Hill-Climbing Algorithm
Many learning systems search through a space of possible performance elements, seeking an element whose expected utility, over the distribution of problems, is high. As the task of nding the globally optimal element is often intractable, many practical learning systems instead hill-climb to a local optimum. Unfortunately, even this is problematic as the learner typically does not know the under...
متن کاملA simulated annealing and hill-climbing algorithm for the traveling tournament problem
The Traveling Tournament Problem (TTP) [E. Easton, G. Nemhauser, M. Trick, The traveling tournament problem description and benchmarks, in: Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming, CP 2001, 2001, pp. 580–584; M. Trick, Challenge Traveling Tournament Problems, 2004] schedules a double round-robin tournament to minimize the total distan...
متن کاملA Heuristic for Domain Independent Planning and its Use in an Enforced Hill-climbing Algorithm
We present a new heuristic method to evaluate planning states, which is based on solving a relaxation of the planning problem. The solutions to the relaxed problem give a good estimate for the length of a real solution, and they can also be used to guide action selection during planning. Using these informations, we employ a search strategy that combines Hill-climbing with systematic search. Th...
متن کاملTEM Color Image Segmentation using Hill Climbing Algorithm
TEM image is rapidly gaining prominence in various fields. Since high resolution TEM image captures huge amount of information, it is important to understand image segmentation techniques on it. The goal of image segmentation is to cluster pixels into salient image regions, i.e., regions corresponding to individual surfaces, objects, or natural parts of objects. To have region based image retri...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Artificial Intelligence & Applications
سال: 2014
ISSN: 0976-2191,0975-900X
DOI: 10.5121/ijaia.2014.5103