In this study we use Genetic Programming (GP) as an offline hyper-heuristic to evolve a mutation operator for Evolutionary Programming. This is done using the Gaussian and uniform distributions as the terminal set, and arithmetic operators as the ...

Population diversity is essential for the effective use of any crossover operator. We compare seven commonly used diversity mechanisms and prove rigorous run time bounds for the (μ+1) GA using uniform crossover on the fitness function Jump_k. All ...

Network design problems have been largely studied in the last decades due to the ubiquity of IT communication in our daily life. We address in this paper the k-edge-connected hop-constrained network design problem (kHNDP) which is known to be NP-hard. ...

In molecular biology, the subject of protein structure prediction is of continued interest, not only to chart the molecular map of living cells, but also to design proteins with new functions. The Inverse Folding Problem (IFP) of finding sequences that ...

In this paper we present a challenging problem that many decision makers in coal mining industry face. The coal processing and blending problem (CPBP) builds upon the traditional blending problem known in operations research (OR) by including decision ...

Reinforcement Learning agents with memory are constructed in this paper by extending neuroevolutionary algorithm NEAT to incorporate LSTM cells, i.e. special memory units with gating logic. Initial evaluation on POMDP tasks indicated that memory ...

In an evolutionary system, robustness describes the resilience to mutational and environmental changes, whereas evolvability captures the capability of generating novel and adaptive phenotypes. The research literature has not seen an effective ...

Maintaining population diversity has long been considered fundamental to the effectiveness of evolutionary algorithms. Recently, with the advent of novelty search, there has been an increasing interest in sustaining behavioral diversity by using both ...

An unsolved problem in neuroevolution (NE) is to evolve artificial neural networks (ANN) that can store and use information to change their behavior online. While plastic neural networks have shown promise in this context, they have difficulties ...

Recent advances in geometric semantic genetic programming (GSGP) have shown that the results obtained by these methods can outperform those obtained by classical genetic programming algorithms, in particular in the context of symbolic regression. ...

To provide sustainable and efficient urban logistics and transportation services, urban mobility tools are facing challenges on reducing carbon emission, waiting time for passengers and transit time. The emergence of many new intelligent and electric ...

As the field of data science continues to grow, there will be an ever-increasing demand for tools that make machine learning accessible to non-experts. In this paper, we introduce the concept of tree-based pipeline optimization for automating one of the ...

While evolutionary algorithms (EAs) have long offered an alternative approach to optimization, in recent years backpropagation through stochastic gradient descent (SGD) has come to dominate the fields of neural network optimization and deep learning. ...

The evolution of Boolean functions that can be used in cryptography is a topic well studied in the last decades. Previous research, however, has focused on evolving Boolean functions directly, and not on general methods that are capable of generating ...

In an age-layered evolutionary algorithm, candidates are evaluated on a small number of samples first; if they seem promising, they are evaluated with more samples, up to the entire training set. In this manner, weak candidates can be eliminated quickly,...

In fighting games, players can perform many different actions at each instant of time, leading to an exponential number of possible sequences of actions. Some of these combinations can lead to unexpected behaviors, which can compromise the game design. ...

Typography plays a key communication role in the contemporary information-dense culture. Type design is a central, complex, and time consuming task. In this work we develop the generative system to type design based on an evolutionary algorithm. The key ...

A new indirect scheme for encoding neural network connection weights as sets of wavelet-domain coefficients is proposed in this paper. It exploits spatial regularities in the weight-space to reduce the gene-space dimension by considering the low-...

Grammar-based Genetic Programming systems are capable of generating identical phenotypic solutions, either by creating repeated genotypic representations, or from distinct genotypes, through their many-to-one mapping process. Furthermore, their ...

The migraine disease is a chronic headache presenting symptomatic crisis that causes high economic costs to the national health services, and impacts negatively on the quality of life of the patients. Even if some patients can feel unspecific symptoms ...