LTLf Synthesis

LTLf synthesis focuses on automatically generating strategies for agents to achieve goals specified in Linear Temporal Logic over finite traces (LTLf), considering potential interactions with an environment. Current research emphasizes efficient algorithms, such as those based on on-the-fly deterministic automata construction and DPLL-inspired search, to overcome the computational complexity inherent in LTLf synthesis, exploring both terminating and non-terminating transducer representations for strategies. This field is significant for its applications in diverse areas like robotics, clinical trial data analysis, and service composition, offering solutions for automated system design and control under uncertainty.