## Data Structures in Natural Computing: Databases as Weak or Strong Anticipatory Systems

Citations: | 1 - 1 self |

### BibTeX

@MISC{Rossiter_datastructures,

author = {B. N. Rossiter and M. A. Heather},

title = {Data Structures in Natural Computing: Databases as Weak or Strong Anticipatory Systems},

year = {}

}

### OpenURL

### Abstract

Abstract. Information systems anticipate the real world. Classical databases store, organise and search collections of data of that real world but only as weak anticipatory information systems. This is because of the reductionism and normalisation needed to map the structuralism of natural data on to idealised machines with von Neumann architectures consisting of fixed instructions. Category theory developed as a formalism to explore the theoretical concept of naturality shows that methods like sketches arising from graph theory as only non-natural models of naturality cannot capture real-world structures for strong anticipatory information systems. Databases need a schema of the natural world. Natural computing databases need the schema itself to be also natural. Natural computing methods including neural computers, evolutionary automata, molecular and nanocomputing and quantum computation have the potential to be strong. At present they are mainly at the stage of weak anticipatory systems.