Timofey Tomashevskiy

Proactive Context-Forecasted Safety Constraints for Nonstationary Reinforcement Learning

Pro proactive constraint generation substantially reduces collisions under both seen and out-of-training nonstationarity intensities and generally remains effective across held-out driving layouts while maintaining usable task performance, suggesting that context-based constraint generation is a promising approach for...