Communication Minimization via Emergent Signaling: Resource-Aware Semantic Compression

Wang et al. and Affinita et al. highlight severe communication limitations in disaster scenarios, but existing solutions focus on technical optimization. We propose agents learn to communicate only the "information-theoretic essence" of coordination needs. Inspired by Qiu et al.'s intention propagation but with a radical efficiency focus, agents would develop emergent signaling systems where minimal transmissions trigger complex coordinated behaviors. For instance, in post-catastrophe environments with 99% packet loss (Shi et al.), a single "chirp" could encode an entire multi-agent plan through learned mappings. This differs from standard event-triggering (Cheng & Li) by optimizing for semantic content rather than transmission frequency. The approach draws from linguistic minimalism and could revolutionize operations in communication-denied environments, from underground robotics to interplanetary exploration.

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