2 optimization "DIFFER" PhD positions

2 Doctoral Researchers in Reinforcement Learning

Aalto University | Helsinki, Uusimaa | Finland | 1 day ago

-ergodic dynamics, such an average may differ arbitrarily from what the individual agent experiences as it lives out one trajectory over time. Furthermore, RL typically seeks a time-invariant policy that

Doctoral Researchers in Reinforcement Learning

AALTO UNIVERSITY | Finland, | Finland | 18 days ago

reset, failures can be irreversible, and the real world keeps changing. Standard RL finds policies by optimizing over many hypothetical futures. Under non-ergodic dynamics, such an average may differ