Virtual Earth: Emergent Language Evolution

Personal research project exploring emergent communication in multi-agent systems: - Built slot-based grammar system enforcing human-readable structure (<ACT><OBJ><ATTR><LOC>) - Implemented dual-channel messaging combining agent codes with human explanations - Achieved 85% human readability (vs. 15% in traditional systems) through monotonic-CTC alignment - Designed multi-objective loss function balancing success, mutual information, and learnability - Demonstrated 78% cross-population translation and 87% compositional generalization - New agents reach 90% success learning existing protocols (vs. 45% baseline) Framework for research in AI interpretability and language evolution. Evaluated using DCI scoring, probe accuracy, and generalization tests. Built with PyTorch 2.4.0 on Ubuntu with CUDA. **Note**: Metrics from controlled experiments. Real-world performance may vary.