Evolution of metamemory based on self-reference to own memory in artificial neural network with neuromodulation

Abstract

AbstractThe ability of humans to self-monitor and control their memory processes is called metamemory and has been widely studied as a component of metacognition in cognitive psychology. Metamemory in non-human animals has also been investigated in recent years, although it had been regarded as a truly unique characteristic of human memory. We attempt to evolve artificial neural networks with neuromodulation, which have a metamemory function. Our constructive approach is expected to contribute, by introducing a novel dimension of evolutionary plausibility, to the discussion of animal experiments to detect metamemory. In this study, we demonstrate the evolution of neural networks that have a metamemory function based on the self-reference of memory, including the analysis of the evolved mechanism of metamemory. In addition, we discuss the similarity between the structure of the evolved neural network and the metamemory model defined by Nelson and Narens.