composite agent pattern

An Explorer-Scientist Pattern is a composite agent pattern that combines exploratory curiosity with systematic observation and measurement, creating AI agents capable of venturing into unknown territories while rigorously documenting and analyzing their findings.

• AKA: Discovery-Analysis Pattern, Exploration-Observation Agent.
• Context:
  • It can combine the Explorer dimension providing curiosity and boundary-pushing with the Scientist dimension adding systematic observation and rigor.
  • It can enable agents to discover new problem spaces while maintaining scientific methodology.
  • It can balance creative exploration with methodical documentation.
  • It can be part of a Nine Dimensions Framework for cognitive agent design.
• Example(s):
  • Drug Discovery Agent that explores molecular structures while testing compounds.
  • System Vulnerability Explorer that probes boundaries while documenting patterns.
  • Market Pattern Analyst that discovers anomalies while building predictive models.
• Counter-Example(s):
  • Single-Dimension Agent that only explores or only analyzes.
  • Revolutionary-Builder Pattern that focuses on transformation rather than discovery.
  • Static Analysis System that lacks exploratory capability.
• See: Composite Agent Pattern, Nine Dimensions Framework, Scientific Method, Exploration-Exploitation Tradeoff.