Comparing different control architectures for autobiographic agents in static virtual environments

This paper highlights the effectiveness of autobiographic memory applied to an autonomous agent from an Artificial Life perspective. A virtual experimental-based approach deals with different implementation designs of control architectures for autobiographic agents, including detailed measurements of the agents' lifetimes compared with purely reactive agents, running in two distinct static environments. Experimental results produce evidence which confirms the research hypothesis that autobiographic memory can prove beneficial, indicating increases in the lifetime of an autonomous, autobiographic, minimal agent. In particular, both Trace-back and Locality autobiographic memory architectures, with or without noise interference, showed superiority over purely reactive control.