2 papers
cs.LG2026
Unsupervised Learning of Efficient Exploration: Pre-training Adaptive Policies via Self-Imposed Goals
Octavio Pappalardo
Unsupervised pre-training can equip reinforcement learning agents with prior knowledge and accelerate learning in downstream tasks. A promising direction, grounded in human develop…
cs.LG2026
Black Box Meta-Learning Intrinsic Rewards
Octavio Pappalardo, Rodrigo Ramele, Juan Miguel Santos
The broader application of reinforcement learning (RL) is limited by challenges including data efficiency, generalization capability, and ability to learn in sparse-reward environm…