Optimizing Associative Information Transfer within Content-addressable Memory
Mikhail Prokopenko, Daniel Polani and Peter Wang
This paper investigates an information-theoretic design principle, intended to support an evolution of a memory structure fitting a specific selection pressure: associative information transfer through the structure. The proposed criteria measure how much does associativity in memory add to the information transfer in terms of precision, recall and effectiveness. The study also introduces a conjectural analogy between memory retrieval and self-replication, with DNAas a partially-associative memory containing relevant information. DNA decoding by a complicated protein machinery (“cues” or “keys”) may correspond to an associative recall: i.e., a replicated offspring is an associatively-recalled prototype. The proposed information-theoretic criteria intend to formalize the notion of information transfer involved in self-replication, and enable bio-inspired design of more effective memory structures.