Agentic AI Reference Architecture

Cognition · Software component

Environment Simulator

Software componentCognitionCognition & Memoryarc:EnvironmentSimulator

A forward model that, given a state and action, returns legal actions, a sampled successor state (drawn from its outcome distribution when stochastic) and terminal status for planning simulations.

Responsibility. Generates simulated state transitions for search and rollouts.

Also known as: Forward model, Simulator, Generative model, Training environment, Simulation environment, Grid world

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Direct neighbourhood (hover for relationship types)

Relationships

is configured by structural

is invoked by dependency

Design guidance

Classification

Patterns
Stochastic outcome samplingSelf-playEpisode resetSim-to-real transfer
Risks mitigated
Costly or unsafe real-world exploration

Sources

  1. Ch5.5: T. Nguyen, "Monte Carlo Tree Search Fundamentals," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 5.5. ISBN: 9798244538229.
  2. Ch5.12: T. Nguyen, "Learning-Based Decision Making Fundamentals," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 5.12. ISBN: 9798244538229.
  3. Ch5.13: T. Nguyen, "Hybrid Decision Systems Fundamentals," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 5.13. ISBN: 9798244538229.