memorysimulation
Memory simulation refers to the computational modeling of memory processes in order to understand, predict, or reproduce how memories are formed, stored, retrieved, and forgotten. It covers work aimed at explaining human memory phenomena as well as the development of memory systems for artificial agents. In cognitive science, memory simulators implement theories of memory architecture—such as working memory, episodic memory, and semantic memory—and use simulated tasks to compare predictions with human data. In artificial intelligence and robotics, memory simulation often focuses on designing memory architectures that allow agents to retain and retrieve past experiences, enhancing long-term autonomy and planning.
Common approaches include symbolic and rule-based models (ACT-R, Soar, the Atkinson-Shiffrin framework) and connectionist or neural
Applications span experimental psychology to test hypotheses about memory, clinical research on aging and amnesia, and