研究有限智能体如何在记忆与通信间权衡，找到最优信息分配策略。
Memory Is Communication: The Frontier Between Remembering and Signaling
- 提出记忆-通信前沿概念，刻画历史与同伴信息的协同效率边界。
- 实验显示重复目标可缩短成功消息长度，但隐含循环规则无效。
- 适合对认知架构、协作智能系统感兴趣的读者参考。
受限智能体可通过自身历史或同伴信息进行决策。保留任务相关的历史可减少后续通信，而同伴消息可补足记忆不足。在资源双重受限下，如何分配信息预算？给定固定任务与决策规则，达到性能阈值的记忆与消息速率组合构成可达区域，其高效边界称为记忆-信号前沿。我们假设：当历史能带来相同最大任务损失降低时，记忆收益越大，所需同伴通信越少。初步参照游戏中，目标重复与消息变短相关，而隐藏循环规则的可预测性未缩短消息。通过调节记忆与消息速率的实验，可估计该前沿并验证此预测在协作任务中的普适性。
原文摘要 · Abstract (English)
A bounded agent may obtain information for a decision from its own past, from peers, or from both sources. Retaining task-relevant history can reduce later communication, while a peer message can supply what memory lacks. Under limits on both resources, how should an agent allocate its information budget? Given a fixed task and decision rule, the memory and message rate pairs attaining a performance threshold form an achievable region under specified rules for using history and peer observations. We call its efficient boundary the remembering--signaling frontier. Across conditions where history permits the same maximum reduction in task loss, we hypothesize that a bounded agent will need less peer communication when it obtains a larger loss reduction from history. In preliminary referential games, target repetition coincided with shorter successful messages, while predictability from a hidden cyclic rule did not shorten them. Experiments varying memory and message rates can estimate the frontier and test this prediction across cooperative tasks.
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