Beyond the Centralized Mindset Mitchel Resnick Epistemology and Learning Group MIT Media Lab

Sciences of Complexity Complex phenomena arising from simple interactions among simple parts Research in: Chaos Self-organization Adaptive systems Nonlinear dynamics Artificial Life

Decentralized Models Flocks Of Birds Traditionally, people assumed that their was a leader bird at the front of the flock Now, new theories view flocks as decentralized and self-organizing Each bird follows a certain set of rules, reacting to the other birds and the flock patterns arise from these simple, local interactions.

Resnick’s Approach – Helping students understand decentralized systems Probing student’s conceptions Developing new conceptual tools Developing new computational tools

Starlogo Goals: To let students investigate the ways that complex patterns can arise from interactions among individual creatures To enable students to build their own models

Starlogo, cont’d An extension of Logo with: More turtles – can have thousands of creatures working in parallel Turtles have better “senses” – the senses allow the turtles to interact with each other and the environment More complex turtle world – the environment has capabilities for interactions as well

Termite Example Initial: Later:

Projects with Star Logo Traffic Jams Rules: If there is a car close ahead, slow down If there are not any cars close ahead, speed up (unless you are at the speed limit) If you detect a radar trap, slow down What if there isn’t a radar trap? With just the first two rules what do you expect to happen? Why? Termites and Wood Chips Ant Cemeteries

Decentralized Thinking Student’s work with Starlogo provided evidence of a strong centralized mindset Projects such as Starlogo may allow for a change in typical ways of thinking about projects Models allow for complex ideas to be presented to students of younger ages

Decentralized thinking Positive Feedback Crucial role in decentralized phenomena Example: Silicon Valley Randomness “Seeds” aren’t necessary to initiate patterns and structures Self-organizing systems can create their own seeds, and hence randomness plays an important role

Decentralized thinking, cont’d Idea of Levels is important A flock isn’t a big bird – interactions among birds give rise to a flock, interactions among cars make a traffic jam Objects on one level behave differently than objects on another level (cars move forward, traffic jams move back) Objects aren’t always a collection of parts A traffic jam is an “emergent object,” emerging from the interactions among lower-level objects

Decentralized thinking, cont’d Richer views of the environment Need to think of the environment as something that you can interact with The path of an ant walking on a beach may be complex, but that complexity isn’t a reflection on the ant, but of the environment. (Herbert Simon, Sciences of the Artificial)

Related Work Exploring Emergence The Virtual Fish Tank Online “Active Essay” http://el.www.media.mit.edu/groups/el/projects/emergence/index.html The Virtual Fish Tank The Computer Museum, Boston http://www.tcm.org/html/fishtank/vft_walkthrough.html

Flocks, Herds and Schools: A Distributed Behavioral Model

Display and Animation - Approaches Simulation - Particle Systems - Individual Scripting - Simulation of individual birds Simulation - Particle Systems - Boid flocks - Geometrical Object - Visually Significant - Orientation - Complexity - Interaction

Necessities for Flocking The geometric ability to fly - “dynamic, incremental, rigid, geometrical transformation of an object moving along and tangent to a 3-D curve” - Or, as we like to call it, a flying Boid - Local space and coordinates - Translation, pitch, yaw Banking - The Roll

Natural Flocks Motivations Complexity A desire to stay close to the flock Evolutionary pressures A desire to avoid collisions Complexity No apparent overload function Constant time algorithm

Simulated Flocks -Complexity Simulation O(n^2) Limits size of flocks Collision Avoidance Velocity matching Flock Centering Localized perception Bifurcation

Simulated Flocks (cont’d) Decision making Acceleration Requests Strengths To average or not to average? Expert Systems Prioritized acceleration allocation

Behavior Motivations reach a steady state Add obstacles Flock is in harmony, each boid having balanced its desires Flock is also very boring Add obstacles Complexity of natural flock determined by complexity of the natural environment

Environmental Obstacles Force Field Angles Strength discrepancy and panic Steer-to-Avoid

Other Applications - Schools Herds Traffic Patterns (Jams, in southern CA)

Jude Battista Kendra Knudtzon ArtiFishial Life Jude Battista Kendra Knudtzon

ArtiFishial Life Project Fish schooling Interactive Java applet exploring emergence, self-adaptation, and artificial life Graphical representation where physical characteristics reflect behavior Educational Focus