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cs.AI2026
Progress Constraints for Reinforcement Learning in Behavior Trees
Finn Rietz, Mart KartaÅ¡ev, Petter Ãgren +1
Behavior Trees (BTs) provide a structured and reactive framework for decision-making, commonly used to switch between sub-controllers based on environmental conditions. Reinforceme…
cs.AI2024
Prioritized Soft Q-Decomposition for Lexicographic Reinforcement Learning
Finn Rietz, Erik Schaffernicht, Stefan Heinrich +1
Reinforcement learning (RL) for complex tasks remains a challenge, primarily due to the difficulties of engineering scalar reward functions and the inherent inefficiency of trainin…