Abstract
We investigate the correlation between the information theoretic
measure of empowerment and the graph theoretic measure
of closeness centrality, to better understand the structural
conditions that must exist in a world for learning and
adaptation. We examine both measures in both a simple gridworld
scenario, represented as a graph, and on a scale-free
graph. We show a strong correlation between the two measures,
and discuss the strengths and weaknesses of both. We
go on to show how the local measurement of empowerment
can in many cases predict a measure for the global measurement
of closeness centrality.
measure of empowerment and the graph theoretic measure
of closeness centrality, to better understand the structural
conditions that must exist in a world for learning and
adaptation. We examine both measures in both a simple gridworld
scenario, represented as a graph, and on a scale-free
graph. We show a strong correlation between the two measures,
and discuss the strengths and weaknesses of both. We
go on to show how the local measurement of empowerment
can in many cases predict a measure for the global measurement
of closeness centrality.
| Original language | English |
|---|---|
| Title of host publication | Artificial Life XI |
| Subtitle of host publication | Procs of the 11th Int Conf on the Simulation and Synthesis of Living Systems |
| Editors | Seth Bullock, Jason Noble, Richard Watson, Mark A. Bedau |
| Publisher | MIT Press |
| Pages | 25-32 |
| ISBN (Print) | 978-0-262-75017-2 |
| Publication status | Published - 2008 |