Agent Semantics, Semantic Spacetime, and Graphical Reasoning

Burgess, Mark

arXiv.org Artificial Intelligence 

Semantic Spacetime (SST) is a discrete, graph theoretic'agent' representation of configurations and process phenomena, used for modelling scenarios that include knowledge representations, in the form of labelled directed graphs [1-4]. It enables both qualitative and quantitative interpretations of processes by combining physical and virtual concepts (from physics and information science) into a Promise Theoretic agent model [5]. Promise Theory principles emphasize the autonomy or locality of causal behaviour, so there are clear motivations for modelling phenomena in this way. As a graph theoretical structure, a Semantic Spacetime is a collection of nodes (agents) joined by links (channels for process information), both of which may have annotations and numerical values associated with them. A key application for Semantic Spacetime in artificial systems is to represent'knowledge' (in its simplified sense) and process structures, such as those normally associated with indexing methods or Semantic Webs, like the triple store approaches of the Resource Description Framework (RDF) [6].

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