57 citations · 155 across the 48 of their papers we have counts for
4 papers · 1 filter
Sensor to Pixels: Decentralized Swarm Gathering via Image-Based Reinforcement Learning
Yigal Koifman, Eran Iceland, Erez Koifman +2
This study highlights the potential of image-based reinforcement learning methods for addressing swarm-related tasks. In multi-agent reinforcement learning, effective policy learni…
VariAntNet: Learning Decentralized Control of Multi-Agent Systems
Yigal Koifman, Erez Koifman, Eran Iceland +2
A simple multi-agent system can be effectively utilized in disaster response applications, such as firefighting. Such a swarm is required to operate in complex environments with li…
A model is worth tens of thousands of examples
Thomas Dagès, Laurent D. Cohen, Alfred M. Bruckstein
Traditional signal processing methods relying on mathematical data generation models have been cast aside in favour of deep neural networks, which require vast amounts of data. Sin…
From Compass and Ruler to Convolution and Nonlinearity: On the Surprising Difficulty of Understanding a Simple CNN Solving a Simple Geometric Estimation Task
Thomas Dagès, Michael Lindenbaum, Alfred M. Bruckstein
Neural networks are omnipresent, but remain poorly understood. Their increasing complexity and use in critical systems raises the important challenge to full interpretability. We p…