[Tyler]

Intelligence from Causal Entropic Forces
24 April 2013, 7:01 pm

 

You may recall our 2012 story, The Universe, The Internet, and the Brain about a paper identifying similarities between the structure and dynamics of the brain and the universe. Now, a new paper from Dr. Alex Wissner-Gross proposes a more dramatic connection: universes that produce more entropy (or disorder) over their lifetimes tend to have more favorable properties for the existence of intelligent beings. The paper describes how two attributes of intelligence, tool use and social cooperation, emerge spontaneously in simple physical system due to "causal entropic forces". According to the paper, these forces provide the motivation behind adaptive behavior. From the paper:

Recent advances in fields ranging from cosmology to computer science have hinted at a possible deep connection between intelligence and entropy maximization. In cosmology, the causal entropic principle for anthropic selection has used the maximization of entropy production in causally connected space-time regions as a thermodynamic proxy for intelligent observer concentrations in the prediction of cosmological parameters. In geoscience, entropy production maximization has been proposed as a unifying principle for nonequilibrium processes underlying planetary development and the emergence of life. In computer science, maximum entropy methods have been used for inference in situations with dynamically revealed information, and strategy algorithms have even started to beat human opponents for the first time at historically challenging high look-ahead depth and branching factor games like Go by maximizing accessible future game states

For more details, including the math, see the short paper, which was published in the 19 April 2013 issue of Physical Review Letters, Causal Entropic Forces (PDF format). You can also read a longer Inside Science article about the ideas in the paper along with comments from other researchers, Physicist Proposes New Way To Think About Intelligence. Or read on to see a short video showing software demonstrations of simple systems driven by entropic forces that spontaneously learn pole balancing, a simplified type of tool use, and social interaction.

Source: robots.net

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