Enhance Simulator Scientific Accuracy and Scale

[google-labs-jules]

The "Dynamic Retrocausal Simulator" has been significantly enhanced to improve its scientific accuracy and scalability.

Key improvements include:

1. True Temporal Predictions: Agents now maintain a rolling history of their state, providing actual temporal sequences to the TCN instead of repeated current states.
2. Causal TCN Architecture: The TCN model now correctly implements causal convolution by using explicit padding and temporal shifting, matching standard practices for sequence forecasting.
3. Multi-Agent Retrocausality: All agents now utilize predictive modeling to adjust their behavior, creating a more complex and realistic system of future-aware interactions.
4. Scalability: The simulator defaults have been updated to 30 agents on a 10x10 grid, consistent with the project's documentation.
5. Modern API Compatibility: The code has been updated to be fully compatible with Mesa 3.x, utilizing the new AgentSet API for better performance and future-proofing.
6. Robust Tracking: New telemetry features in RetroModel provide accurate tracking of total collisions and specific agent-level collision metrics.

Verified with simulation tests.

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PR created automatically by Jules for task 447626770133282272 started by @markfxm

[google-labs-jules]

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