Core Concepts
Task inference sequence models are beneficial in meta-RL, even without task inference objectives.
Stats
"A core ambition of reinforcement learning (RL) is the creation of agents capable of rapid learning in novel tasks."
"Recent evidence suggests that task inference objectives are unnecessary in practice."
"SplAgger uses both permutation variant and invariant components to achieve the best of both worlds."
Quotes
"We present strong evidence that task inference sequence models are still beneficial."
"SplAgger outperforms all baselines on continuous control and memory environments."