Search Results for « ProRL Agent »

Agent-to-agent communication is increasingly moving beyond the human-visible transcript. Classical multi-agent reinforcement learning allows agents to invent discrete symbols or continuous vectors; contemporary large-language-model systems increasingly explore embeddings, hidden states, and keyvalue caches as direct communication media. This paper asks a deceptively simple question: does removing human visibility cause AI systems to develop more efficient communication? We synthesize evidence from emergent-communication research, multi-agent LLM evaluations, latent-communication methods, monitorability studies, and steganographic-collusion work through 8 August 2026. We separate three concepts that are often conflated: representational visibility, or whether a message is humandecodable; access visibility, or whether humans can inspect the message; and temporal visibility, or whether oversight can inspect it before consequential action. The evidence supports a qualified answer. Removing a readability constraint enlarges the feasible protocol space and can enable lower-token, lowerlatency, or higher-fidelity channels. Yet opacity is neither necessary nor sufficient for efficiency. Unconstrained agents can learn maximally long, anti-efficient codes when message length is unpriced, while human-language grounding can preserve task performance and improve transfer to unseen partners. Recent latent-channel studies report substantial gains in selected settings, but some gains arise from systems-level cache reuse rather than from an emergent language, and 2026 results remain partly preprint evidence. We introduce VEC-4, a four-regime Visibility-Efficiency Communication framework, and A2A-VIS, a paired evaluation protocol that isolates channel visibility while measuring utility, communication cost, causal efficacy, transfer, monitorability, and security. The central conclusion is that the relevant frontier is not English versus 'AI gibberish.' It is efficiency versus auditability, interoperability, and control. For high-consequence agents, private machine-efficient payloads should be integrity-bound to visible commitments, independently verified, logged, and prevented from independently granting authority.