Feasibility of a minimalistic evolutionary system with simultaneous adaptation, unbounded complexity growth, spatial interactions, and efficiency

Determine whether a minimalistic artificial chemistry modeled in the Hash Chemistry framework can be constructed to simultaneously exhibit continuous adaptation of self-replicating patterns, unbounded growth of complexity measured by self-replicator size, explicit multiscale spatial ecological interactions among evolving patterns, and computational efficiency within a single model framework.

Background

Hash Chemistry and its variants explore open-ended evolution using a hash function as an oracle for evaluating higher-order entities. The non-spatial variant demonstrated continuous adaptation and unbounded complexity growth but lacked multiscale spatial ecological interactions. Conversely, a prototype cellular version captured spatial interactions but failed to show meaningful adaptive evolution or complexity growth.

The paper frames a central challenge: whether one can create a similar minimalistic evolutionary system that simultaneously achieves adaptation, unbounded complexity growth, spatial ecological interactions, and computational efficiency. The proposed Structural Cellular Hash Chemistry (SCHC) is introduced as an attempt to address this challenge, demonstrating results consistent with these goals.