Evolving Memory: Logical Tasks for Cellular Automata

Complex Systems Modeling
Modeling, Algorithms, and Informatics Group (CCS-3)
Los Alamos National Laboratory, MS B256
Los Alamos, New Mexico 87545, USA
e-mail: rocha@lanl.gov

Citation: Rocha, Luis M. [2004]. "Evolving Memory: Logical Tasks for Cellular Automata". Ninth International Conference on the Simulation and Synthesis of Living Systems (ALIFE9). Boston, Massachusetts, September 12-15th 2004. In Press. Los Alamos National Laboratory Internal Report Number: LAUR 04-0628.

The full paper is available in Adobe Acrobat (.pdf) format only. Due to mathematical notation and graphics, only the abstract is presented here.


We present novel experiments in the evolution of Cellular Automata (CA) to solve nontrivial tasks. Using a genetic algorithm, we evolved CA rules that can solve non-trivial logical tasks related to the density task (or majority classification problem) commonly used in the literature. We present the particle catalogs of the new rules following the computational mechanics framework. We know from that particle computation in CA is a process of information processing and integration. Here, we discuss the type of memory that emerges from the evolving CA experiments for storing and manipulating information. In particular, we contrast this type of evolved memory with the type of memory we are familiar with in Computer Science, and also with the type of biological memory instantiated by DNA. A novel CA rule obtained from our own experiments is used to elucidate the type of memory that one-dimensional CA can attain.

Keywords:Representation, Cellular Automata, Evolutionary Computation, Artificial Life, Cognitive Science, Symbols, Genetic Code, Memory.

For the full paper please download the pdf version

For more information contact Luis Rocha at rocha@indiana.edu.
Last Modified: September 02, 2004