Embedding Symbolic Temporal Knowledge into Deep Sequential Models
Yaqi Xie Fan Zhou Harold Soh Yaqi Xie Fan Zhou Harold Soh
Sequences and time-series often arise in robot tasks, e.g., in activity recognition and imitation learning. In recent years, deep neural networks (DNNs) have emerged as an effective data-driven methodology for processing sequences given sufficient training data and compute resources. However, when data is limited, simpler models such as logic/rule-based methods work surprisingly well, especially w...