In collaborative privacy preserving planning (CPPP), a group of agents jointly creates a plan to achieve a set of goals while preserving each others' privacy. During planning, agents often reveal the private dependencies between their public actions to other agents, that is, which public action facilitates the preconditions of another public action. Previous work in CPPP does not limit the disclosure of such dependencies. In this paper, we explicitly limit the amount of disclosed dependencies, allowing agents to publish only a part of their private dependencies. We investigate different strategies for deciding which dependencies to publish, and how they affect the ability to find solutions. We evaluate the ability of two solvers -- distribute forward search and centralized planning based on a single-agent projection -- to produce plans under this constraint. Experiments over standard CPPP domains show that the proposed dependency-sharing strategies enable generating plans while sharing only a small fraction of all private dependencies.

中文翻译：

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在隐私保护计划中部分披露私人依赖性

在协作式隐私保护计划（CPPP）中，一组代理共同创建一个计划，以实现一组目标，同时保护彼此的隐私。在计划期间，代理通常会向其他代理揭示其公共行为之间的私人依存关系，也就是说，这种公共行为促进了另一个公共行为的前提。CPPP中的先前工作并不限制此类依赖项的公开。在本文中，我们明确限制了公开的依赖项的数量，允许代理仅发布其私有依赖项的一部分。我们研究不同的策略，以确定要发布的依赖项，以及它们如何影响找到解决方案的能力。我们评估了两个求解器的能力-分布前向搜索和基于单主体预测的集中式计划-在此约束下产生计划的能力。在标准CPPP域上进行的实验表明，提出的依赖关系共享策略可以生成计划，同时仅共享所有私人依赖项的一小部分。