Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
This paper proposes a hybrid genetic algorithm for multiple sequence alignment. The algorithm evolves guide sequences and aligns input sequences based on the guide sequences. It a...
Genetic algorithms (GAs) have recently become very popular by solving combinatorial optimization problems. In this paper, we propose an extension of the hybrid genetic algorithm f...
Action set selection in Markov Decision Processes (MDPs) is an area of research that has received little attention. On the other hand, the set of actions available to an MDP agent...
In this paper, we propose a simple genetic algorithm for finding the optimal conformation of a protein using the three-dimensional square HP model. A backtracking procedure is use...
Segmentation of medical images is challenging due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. Consequently, this task involves ...
In this paper an evolutionary algorithm is used for evolving gaits in a walking biped robot controller. The focus is fast learning in a real-time environment. An incremental appro...
The application of Artificial Intelligence described in this article is intended to resolve the issue of speculation on the stock market. Genetic Algorithms is the technique that ...
David de la Fuente, Alejandro Garrido, Jaime Lavia...
Genetic Algorithms have widely been used for solving optimization problems in stationary environments. In recent years, there has been a growing interest for investigating and imp...
Candlestick analysis, a form of stock market technical analysis, is well suited for use with a genetic search algorithm. This paper explores an implementation of marrying these tw...