Reinforcement learning agents can generalize better by treating context as a first-class primitive that distinguishes slow-changing external factors from fast-changing internal ones and incorporates abstract high-level descriptors.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Contextual Intelligence The Next Leap for Reinforcement Learning
Reinforcement learning agents can generalize better by treating context as a first-class primitive that distinguishes slow-changing external factors from fast-changing internal ones and incorporates abstract high-level descriptors.