High-quality product quality prediction is very important for iron and steel enterprises to ensure stable production. However, most existing prediction methods are manually designed learning models. These methods consider only macroscopic data while ...

Quality-Diversity (QD) optimization has proven to yield promising results across a broad set of applications. However, QD approaches struggle in the presence of uncertainty in the environment, as it impacts their ability to quantify the true performance ...

Deep convolutional neural networks (DCNNs) have achieved surpassing success in the field of computer vision, and a number of elaborately designed networks refresh the performance records in benchmark datasets. Recently, evolutionary neural architecture ...

Deep convolutional neural networks have become a dominant solution for numerous image classification tasks. However, a main criticism is the poor explainability due to the black-box characteristic, which hurdles the extensive usage of deep convolutional ...

An attack–defense confrontation problem arises from a robot swarm attacking a territory protected by another one. In denied environments, global positioning and communication are hardly available. It becomes difficult for a swarm to realize ...

The design space exploration (DSE) of fault-tolerant multiprocessor systems is very complex, as it contains three interacting NP-hard problems: 1) task hardening; 2) task mapping; and 3) task scheduling. In addition, replication-based task hardening can ...

With the continuous development of computer and electronics, the idea of artificial intelligence has been integrating into the fault tolerance research. As a valuable and prospective intelligent fault tolerance technique in high reliability and high ...

We describe an experimental platform that uses differential evolution to automatically discover high-performance multirotor controllers. All control parameters are tuned simultaneously, no modeling is required, and, as the evolution occurs on a real ...

A novel neuro-evolutionary Cartesian genetic programming-based frame size estimator for multimedia streaming applications has been proposed in this letter. The frame size obtained from the proposed estimator is used to calculate and allocate the bandwidth ...

Uncertain and unpredictable faults can occur in electronic systems that work in harsh environments. Analog circuits play an important part in modern electronic systems. Accordingly, it is important to investigate the reliability of analog circuits under ...

This paper examines the fitness landscape for evolutionary algorithms evolving cellular automata (CA) rules to satisfy an apoptotic fitness function. This fitness function requires the automata to grow as rapidly as possible and to die out by a fixed ...

The reality gap, which often makes controllers evolved in simulation inefficient once transferred onto the physical robot, remains a critical issue in evolutionary robotics (ER). We hypothesize that this gap highlights a conflict between the efficiency ...

One of the essential benefits of swarm robotic systems is redundancy. In case one robot breaks down, another robot can take steps to repair the failed robot or take over the failed robot's task. Although fault tolerance and robustness to individual ...

Self-organized synchronization is a common phenomenon observed in many natural and artificial systems: simple coupling rules at the level of the individual components of the system result in an overall coherent behavior. Owing to these properties, ...

Swarm robotics draws inspiration from decentralized self-organizing biological systems in general and from the collective behavior of social insects in particular. In social insect colonies, many tasks are performed by higher order group or team ...

This paper introduces Antares, which is a bioinspired algorithm for the construction of a decentralized and self-organized P2P information system in computational grids. This algorithm exploits the properties of ant systems, in which a number of ...

One of the major obstacles to achieving robots capable of operating in real-world environments is enabling them to cope with a continuous stream of unanticipated situations. In previous work, it was demonstrated that a robot can autonomously generate ...

The eight articles in this special issue focus on convergent approaches to the understanding of autonomous mental development. The goal is to promote the effort to build the necessary bridges between research areas to help foster the investigation of ...

Exploratory activities seem to be intrinsically rewarding for children and crucial for their cognitive development. Can a machine be endowed with such an intrinsic motivation system? This is the question we study in this paper, presenting a number of ...

The generation of a complete robotic brain for locomotion based on the utility function (UF) method for behavioral organization is demonstrated. A simulated, single-legged hopping robot is considered, and a two-stage process is used for generating the ...