AI RESEARCH
On Tackling Complex Tasks with Reward Machines and Signal Temporal Logics
arXiv CS.AI
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ArXi:2604.14440v1 Announce Type: new We propose a Reinforcement Learning (RL) based control design framework for handling complex tasks. The approach extends the concept of Reward Machines (RM) with Signal Temporal Logic (STL) formulas that can be used for event generation. The use of STL allows not only a efficient representation of rewards for complex tasks but also guiding the