Genetic Programming and Evolvable Machines is a premier peer-reviewed journal focusing on the exciting field of evolutionary computation, particularly genetic programming (GP) and other machine learning techniques. It provides a platform for researchers and practitioners to share advancements in automated problem-solving using evolutionary methods.
The journal features original research articles covering topics such as GP theory, GP applications, evolvable hardware, and the intersection of evolutionary algorithms with other machine learning techniques like neural networks and deep learning. It also includes papers on real-world applications of GP in areas such as robotics, optimization, and data mining.
Genetic Programming and Evolvable Machines aims to promote the development of novel and effective evolutionary computation techniques. Indexed in major scientific databases, this journal is essential reading for computer scientists, engineers, and researchers interested in the cutting-edge of artificial intelligence and machine learning. Submit your innovative work and contribute to shaping the future of automated problem solving.