Abstract: This article presents a novel knowledge-based genetic algorithm (GA) to generate a collision-free path in complex environments. The proposed algorithm infuses specific domain knowledge into ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. We present an artificial intelligence-guided approach to design durable and chemically ...
Abstract: Genetic algorithm (GA) is a common approach for multi-objective path planning. However, conventional GA performs poorly on large-scale complex maps due to the lack of an efficient ...
This research was supported by the MIT-IBM Watson AI Lab, Army Research Office (ARO) Grant W911NF-17-1-0384, and NIH Grants P41EB027062 and U01 EB014976. E.K. acknowledges support from NSF Graduate ...
ABSTRACT: The main objective of software testing is to have the highest likelihood of finding the most faults with a minimum amount of time and effort. Genetic Algorithm (GA) has been successfully ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results