Automatic Programming of Cellular Automata and Artificial Neural Networks Guided by Philosophy

05/10/2019
by   Patrik Christen, et al.
0

Many computer models such as cellular automata have been developed and successfully applied. However, in some cases these models might be restrictive on the possible solutions or their solution is difficult to interpret. To overcome this problem, we outline an approach, the so-called allagmatic method, that automatically creates and programs models with as little limitations as possible but still maintaining human interpretability. We earlier described a meta-model and its building blocks according to the philosophical concepts of structure (spatial dimension) and operation (temporal dimension). They are entity, milieu, and update function that together abstractly describe the meta-model. By automatically combining these building blocks, new models can potentially be created in an evolutionary computation. We propose generic and object-oriented programming to implement the entities and their milieus as dynamic and generic arrays and the update function as a method. We show two experiments where a simple cellular automaton and an artificial neural network are automatically created and programmed. A target state is successfully evolved and learned in the cellular automaton and artificial neural network, respectively. We conclude that the allagmatic method can create and program cellular automaton and artificial neural network models in an automated manner.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/24/2019

Cybernetical Concepts for Cellular Automaton and Artificial Neural Network Modelling and Implementation

As a discipline cybernetics has a long and rich history. In its first ge...
research
08/31/2020

Individuation and Adaptation in Complex Systems

Complex systems have certain characteristics such as network structures ...
research
05/03/2020

System Metamodel Formalism

Differential equations have been widely and successfully used to describ...
research
03/05/2023

On Modifying a Neural Network's Perception

Artificial neural networks have proven to be extremely useful models tha...
research
06/24/2018

Computational Complexity of Observing Evolution in Artificial-Life Forms

Observations are an essential component of the simulation based studies ...
research
11/09/2022

DeepE: a deep neural network for knowledge graph embedding

Recently, neural network based methods have shown their power in learnin...
research
03/15/2021

Growing 3D Artefacts and Functional Machines with Neural Cellular Automata

Neural Cellular Automata (NCAs) have been proven effective in simulating...

Please sign up or login with your details

Forgot password? Click here to reset