4 Contributo in Atti Convegno

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4.1 Contributo in Atti Convegno (Proceeding) 9867
4.2 Abstract 1900
4.3 Poster 754

Prodotti recenti

Parametrizing GP Trees for Better Symbolic Regression Performance through Gradient Descent

Symbolic regression is a common problem in genetic programming (GP), but the syntactic search carried out by the standard GP algorithm often struggles to tune the learned expressions. On the other hand, gradient-based optimizers can efficiently tune parametric functions by exploring the search space locally. While there is a large amount of research on the combination of evolutionary algorithms and local search (LS) strategies, few of these studies deal with GP. To get the best from both worl...

Leveraging Machine Learning for Terrain Traversability in Mobile Robotics

The problem of traversability of soft terrains is hard to solve due to both the inherent modeling complexity and the related computational cost. In this work a surrogate model is used to describe the behavior of soft soil, thus avoiding explicitly simulating it.We leverage machine learning to train a model on real-world data acquired with the “Archimede” robotic platform in DLR’s Moon-Mars test area in Oberpfaffenhofen, Germany. The model is tested using the Gazebo simulation environment by i...

Unraveling the Factors Influencing Team Learning in New Product Development: Lessons from Failure and Success

In the context of new product development (NPD) projects, this research investigates the determinants of team learning and offers a comparative examination of high-performing and low-performing projects through the lens of fuzzy set qualitative comparative analysis (fsQCA). By incorporating insights from the organizational and team learning literature, the study examines the influence of project characteristics (complexity and uncertainty), team interpersonal characteristics (innovation norms...

Digital alignment and strategic flexibility in shaping business model efficiency: Evidence from SMEs in the manufacturing industry

The purpose of this study is to explore the relationship between digital alignment and business model efficiency in small and medium-sized enterprises (SMEs) in the manufacturing industry in Italy. Digital alignment is operationalized as comprising both strategic decision support and operational support. The research employs a quantitative approach, using regression analysis and a necessary condition analysis on a sample of Italian SMEs. The results show that digital alignment, both in terms ...

Trade-Off Between Real-Time and Classification Performance in Motor Imagery BCI

Brain-Computer Interfaces (BCIs) offer direct communication between the brain and external devices, holding immense potential across various applications. This study focuses on Motor Imagery-based BCIs (MI-BCI), decod- ing neural patterns associated with mentally rehearsed motor actions. Despite their promise, BCIs face challenges in real-world applications, primarily in reliability and complexity. While classification accuracy is a standard metric for BCI perfor- mance, the literature often ...

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