Dane Carnegie Malenfant
@dvnxmvlhdf5.bsky.social
MSc. @mila-quebec.bsky.social and @mcgill.ca in the LiNC lab
Fixating on multi-agent RL, Neuro-AI and decisions
Ēka ē-akimiht
https://danemalenfant.com/
Fixating on multi-agent RL, Neuro-AI and decisions
Ēka ē-akimiht
https://danemalenfant.com/
1/3 Thank you to CIFAR and partners in DSET for bringing me to Banff to speak on my research: The challenge of hidden gifts in multi-agent reinforcement learning arxiv.org/abs/2505.20579. We introduce a novel task on reciprocity with a scarce resource; take what you need, leave what you don’t.
November 3, 2025 at 3:53 PM
1/3 Thank you to CIFAR and partners in DSET for bringing me to Banff to speak on my research: The challenge of hidden gifts in multi-agent reinforcement learning arxiv.org/abs/2505.20579. We introduce a novel task on reciprocity with a scarce resource; take what you need, leave what you don’t.
4/8
To communicate this to a general audience and the #art community, I built a minimal task: two Gaussian bandits. One agent optimizes with entropy; the other doesn’t. Mid-training, the reward distribution jumps.
To communicate this to a general audience and the #art community, I built a minimal task: two Gaussian bandits. One agent optimizes with entropy; the other doesn’t. Mid-training, the reward distribution jumps.
October 7, 2025 at 6:34 PM
4/8
To communicate this to a general audience and the #art community, I built a minimal task: two Gaussian bandits. One agent optimizes with entropy; the other doesn’t. Mid-training, the reward distribution jumps.
To communicate this to a general audience and the #art community, I built a minimal task: two Gaussian bandits. One agent optimizes with entropy; the other doesn’t. Mid-training, the reward distribution jumps.