6533b82ffe1ef96bd129654b
RESEARCH PRODUCT
Safer Reinforcement Learning for Agents in Industrial Grid-Warehousing
Per-arne AndersenOle-christoffer GranmoMorten Goodwinsubject
Artificial neural networkComputer scienceSAFERControl (management)0202 electrical engineering electronic engineering information engineeringReinforcement learning020206 networking & telecommunications02 engineering and technologyMarkov decision processGridOptimal controlIndustrial engineeringdescription
In mission-critical, real-world environments, there is typically a low threshold for failure, which makes interaction with learning algorithms particularly challenging. Here, current state-of-the-art reinforcement learning algorithms struggle to learn optimal control policies safely. Loss of control follows, which could result in equipment breakages and even personal injuries.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2020-01-01 |