This paper reviews the theory and applications of ant algorithms, new methods of discrete
optimization based on the simulation of self-organized colony of biologic ants. The colony …

This paper proposes the design of fuzzy-rule-based systems using continuous ant-colony
optimization (RCACO). RCACO determines the number of fuzzy rules and optimizes all the …

Knowledge-based expert systems are becoming one of the major tools for scientists and
engineers nowadays, since they have many attractive features and can be called upon to …

One of the problems that focus the research in the linguistic fuzzy modeling area is the trade-
off between interpretability and accuracy. To deal with this problem, different approaches …

Due to notable technological convergence that brought about exponential growth in
computer world, Soft Computing (SC) has played a vital role with automation capability …

In this work we present two new multiobjective proposals based on ant colony optimisation
and random greedy search algorithms to solve a more realistic extension of a classical …

This paper proposes a new reinforcement-learning method using online rule generation and
Q-value-aided ant colony optimization (ORGQACO) for fuzzy controller design. The fuzzy …

This paper proposes zero-order Takagi–Sugeno–Kang (TSK)-type fuzzy system learning
using a two-phase swarm intelligence algorithm (TPSIA). The first phase of TPSIA learns …

This paper presents a methodology for the design of fuzzy controllers with good
interpretability in mobile robotics. It is composed of a technique to automatically generate a …

This paper proposes the design of fuzzy controllers by ant colony optimization (ACO)
incorporated with fuzzy-Q learning, called ACO-FQ, with reinforcements. For a fuzzy …