feat(learning): DQN learner for discrete debug environments

[salim4n]

Add a first neural learner path for discrete toy/debug environments.

Acceptance criteria:

• DQN trains against GridWorld or Target2D without users implementing the algorithm;
• metrics include reward, episode length, epsilon/exploration and loss;
• checkpoint save/load supports inference replay;
• CI smoke proves improvement over random on a deterministic demo.