We study the problem of generating arbitrarily large environments to improve the throughput
of multi-robot systems. Prior work proposes Quality Diversity (QD) algorithms as an effective …

Abstract Current Dynamic Texture Synthesis (DyTS) models can synthesize realistic videos.
However, they require a slow iterative optimization process to synthesize a single fixed-size …

Abstract Recent extensions of Cellular Automata (CA) have incorporated key ideas from
modern deep learning, dramatically extending their capabilities and catalyzing a new family …

Texture modeling and synthesis are essential for enhancing the realism of virtual
environments. Methods that directly synthesize textures in 3D offer distinct advantages to the …

Neural Cellular Automata (NCA) is a class of Cellular Automata where the update rule is
parameterized by a neural network that can be trained using gradient descent. In this paper …

Vision Transformers (ViTs) have demonstrated remarkable performance in image
classification tasks, particularly when equipped with local information via region attention or …

Video games are a natural and synergistic application domain for artificial intelligence (AI)
systems, offering both the potential to enhance player experience and immersion, as well as …

Neural cellular automata have been proven effective in simulating morphogenetic
processes. Developing such automata has been applied in 2D and 3D processes related to …

Morphogenesis is the biological process by which an organism grows and takes its form. It is
responsible for the growth and shape of all living things and has historically been studied …

Automatizing optimal neural architectures is an under-explored domain; the majority of deep
learning domains base their architecture on multiplexing different well-known architectures …