The effect of delay-lines on sequence recall - A study of B-RAAM

Abstract: Connectionist models have been criticized for not being able to form compositional representations of recursive data structures such as trees and lists, a matter that has been addressed by models as Elman networks, RAAM and B-RAAM. These architectures seem to have common features with the human short-term memory regarding recall. Both show a strong recency effect; however, the human memory also exhibits a primacy effect due to rehearsal. The problem is that the connectionist models do not have the primacy aspect, which complicates the learning of long-term dependencies. A long-term dependency is when items presented early should affect the behaviour of the model. Learning long-term dependencies is a problem that is hard to address within these architectures. Delay-lines might be used as a mechanism for implementing rehearsal within connectionist models. However, it has not been clarified how the use of delay-lines affects the recency and the primacy aspect. In this thesis, delay-lines are introduced in B-RAAM. This study investigates how the primacy and the recency aspect are affected by the use of delay-lines, aiming to improve the ability to identify long-term dependencies. The results show that by using delay-lines, B-RAAM has both primacy and recency.