  Large language models (LLMs) are recognized as systems that closely mimic
aspects of human intelligence. This capability has attracted attention from the
social science community, who see the potential in leveraging LLMs to replace
human participants in experiments, thereby reducing research costs and
complexity. In this paper, we introduce a framework for large language models
personification, including a strategy for constructing virtual characters' life
stories from the ground up, a Multi-Agent Cognitive Mechanism capable of
simulating human cognitive processes, and a psychology-guided evaluation method
to assess human simulations from both self and observational perspectives.
Experimental results demonstrate that our constructed simulacra can produce
personified responses that align with their target characters. Our work is a
preliminary exploration which offers great potential in practical applications.
All the code and datasets will be released, with the hope of inspiring further
investigations.
