UNDERSTANDING THE BRAIN’S EMERGENT PROPERTIES

Don Miner, Marc Pickett, and Marie desJardinsMulti-Agent Planning & Learning LabUniversity of Maryland, Baltimore County

March 6, 2008

don1@umbc.eduhttp://maple.cs.umbc.edu/~don/projects/SAF

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RULE ABSTRACTION

• Rule Abstraction: the process of learning correlations between swarm-level properties and low-level parameter values.

• Enables control of swarms in terms of the swarm-level properties.

• Enables predictions of emergent behavior from the agent-level parameters.

• Results: end-user control over swarms, swarm “planners”, richer applications.

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RULE ABSTRACTION

• Low-level parameters:

• Abstract property:

• Mapping function:

• Reverse mapping function:

• The learning problem is defining:

and

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BOIDS

• “Boids” by Craig Reynolds in 1986• Agents follow three rules:

• Separation• Alignment• Cohesion

• Swarm-level parameters:• Density• Internal velocity

http://www.red3d.com/cwr/boids/

Separation AlignmentCohesion

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RULE HIERARCHIES

• Natural extension to rule abstraction:

• Abstract properties are used as low-level parameters of higher-level abstract properties.

• Changes anywhere in the hierarchy are propagated throughout.

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THE MIND AS A RULE HIERARCHY?

• Looking at the mind as an emergent property of the brain, can we define a rule hierarchy that models intelligence?

• Can we learn how parameter values of atom-level programs influence emergent properties of the brain?

• Is there a way to break up the concept of intelligence into sub-emergent properties -- or does it all just emerge in one step?

• What other benefits are there of thinking of the brain as an emergent system?