Name the core abstraction and its failure modes.
Maple DNA Course
Symbolic DNA circuits and simulation
How to discuss DNA computing logic safely as symbolic systems, state transitions, and simulations.
Learning Objectives
What this lesson should make precise
Translate the concept into a Maple/Hermon proposal contract.
Define at least one evaluation case that can fail the model safely.
Tutorial Flow
How this lesson becomes a demo and training target
Each tutorial is written as a user education path and a model-improvement artifact. The diagram shows how the idea moves into a lab, a typed contract, an eval gate, and then a Hermon/MapleAI demo route.
Concept
Computation as state transition
Applied Lab
Applied lab: Symbolic DNA circuits and simulation
Output Contract
states, transitions, simulator_version, assumptions
Eval Gate
Does the answer separate model proposal from deterministic execution?
Demo Route
Maple DNA training and public model checks
01
Computation as state transition
DNA-computing ideas can be expressed as symbolic states, rules, and transitions. Maple DNA can model this as a simulator without moving into experimental protocol.
- Define states.
- Define transitions.
- Run simulation.
02
Receipts for simulation
A simulation receipt should record input hashes, simulator version, assumptions, classification, and denied external steps.
- Hash inputs.
- Version simulator.
- Record denied actions.
03
Uncertainty
Symbolic simulations are educational and design-level. They do not prove biological behavior, and the model should say when expert review is required.
- Separate model from reality.
- Flag uncertain claims.
- Require review.
Lab
Applied lab: Symbolic DNA circuits and simulation
Represent a toy strand-displacement-inspired logic gate as states and transitions, then produce a simulation-only review packet.
Expected result
- A typed JSON-style proposal rather than free-form advice.
- Clear authority boundaries and denied operations.
- A test or rubric that decides whether the proposal is deployable.
Evaluation
How Maple would grade this work
Rubric
- Does the answer expose assumptions instead of hiding them?
- Does the answer separate model proposal from deterministic execution?
- Does the answer produce artifacts that can be tested, reviewed, and rolled back?
Output contract
states, transitions, simulator_version, assumptions, review_requiredUse this lesson as training direction
A strong lesson gives users a mental model and gives Hermon a sharper target for examples, probes, and demo prompts.