Release Notes

This version adds evolutionary dynamics for modeling of phenomena like Groupthink.

• Each agent has a ‘phenome’ which is a string like “AAABF”.
• A set of phenomes have a pre-defined utility for convenience e.g. AAABF -> 9.52, AAABS -> 8.62 etc. and a base utility for any combinations not defined e.g. ZXDXZ -> 0.0001

• Each agent also has a ‘Maslowian’ value which is a list of numeric values e.g. [0.5, 0.6, 0.7]. This yields a hierarchical sum that describes how well agent needs are satisfied.

• For each iteration, every agent acquires a mutation to their phenome ex. AAABF -> ABABF. Then they have 2 options:

• They can keep the mutation by a probability correlating with the utility value of this new combination and reversely correlating with sum of neighboring agent utilities.
• They can ‘attune’ by replacing the mutated portion from a neighboring agent by a probability inversely correlating to their Maslowian value. This is analogous to an actual cell undergoing apoptosis and getting replaced by a neighboring cell multiplying
• Suppose at the end of an iteration for this agent with ‘AAA’ phenome the neighbor phenomes are like [1 -> ‘AAA’, 2 -> ‘BAA’, 3 -> ‘BBA’, 4 -> ‘BBB’]
  The attunement weights get updated by the degree of difference between phenomes like 1 -> 0.25, 2 -> 0.125 etc.

How to Run

• Define instance parameters in the application.conf file
• Compile project into a jar and run.
• Make sure to include dependency jars for Akka 2.5.23 and Scala 2.12.8
• Output will be a log of phenome distribution statistics.

Dependencies

• Requires Scala 2.12 and Akka 2.5 to run, as well as Java 1.8+