AIMC Topic: Computer Simulation

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SuPreMo: a computational tool for streamlining in silico perturbation using sequence-based predictive models.

Bioinformatics (Oxford, England)
SUMMARY: The increasing development of sequence-based machine learning models has raised the demand for manipulating sequences for this application. However, existing approaches to edit and evaluate genome sequences using models have limitations, suc...

The Role of Morphological Variation in Evolutionary Robotics: Maximizing Performance and Robustness.

Evolutionary computation
Exposing an evolutionary algorithm that is used to evolve robot controllers to variable conditions is necessary to obtain solutions which are robust and can cross the reality gap. However, we do not yet have methods for analyzing and understanding th...

Comparing Robot Controller Optimization Methods on Evolvable Morphologies.

Evolutionary computation
In this paper, we compare Bayesian Optimization, Differential Evolution, and an Evolution Strategy employed as a gait-learning algorithm in modular robots. The motivational scenario is the joint evolution of morphologies and controllers, where "newbo...

Neural Architecture Search Using Covariance Matrix Adaptation Evolution Strategy.

Evolutionary computation
Evolution-based neural architecture search methods have shown promising results, but they require high computational resources because these methods involve training each candidate architecture from scratch and then evaluating its fitness, which resu...

Force/position tracking control of fracture reduction robot based on nonlinear disturbance observer and neural network.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: For the fracture reduction robot, the position tracking accuracy and compliance are affected by dynamic loads from muscle stretching, uncertainties in robot dynamics models, and various internal and external disturbances.

Exploring functional conservation in silico: a new machine learning approach to RNA-editing.

Briefings in bioinformatics
Around 50 years ago, molecular biology opened the path to understand changes in forms, adaptations, complexity, or the basis of human diseases through myriads of reports on gene birth, gene duplication, gene expression regulation, and splicing regula...

Pressure-Based Soft Agents.

Artificial life
Biological agents have bodies that are composed mostly of soft tissue. Researchers have resorted to soft bodies to investigate Artificial Life (ALife)-related questions; similarly, a new era of soft-bodied robots has just begun. Nevertheless, because...

Approximating Nonlinear Functions With Latent Boundaries in Low-Rank Excitatory-Inhibitory Spiking Networks.

Neural computation
Deep feedforward and recurrent neural networks have become successful functional models of the brain, but they neglect obvious biological details such as spikes and Dale's law. Here we argue that these details are crucial in order to understand how r...

Incorporating temporal information during feature engineering bolsters emulation of spatio-temporal emergence.

Bioinformatics (Oxford, England)
MOTIVATION: Emergent biological dynamics derive from the evolution of lower-level spatial and temporal processes. A long-standing challenge for scientists and engineers is identifying simple low-level rules that give rise to complex higher-level dyna...

Use of artificial intelligence and radio genomics in neuroradiology and the future of brain tumour imaging and surgical planning in low- and middleincome countries.

JPMA. The Journal of the Pakistan Medical Association
Brain tumour diagnosis involves assessing various radiological and histopathological parameters. Imaging modalities are an excellent resource for disease monitoring. However, manual inspection of imaging is laborious, and performance varies depending...