An important open question in human-robot interaction (HRI) is precisely when an agent should decide to communicate, particularly in a cooperative task. Perceptual Control Theory (PCT) tells us that agents are able to cooperate on a joint task simply by sharing the same 'intention', thereby distributing the effort required to complete the task among the agents. This is even true for agents that do not possess the same abilities, so long as the goal is observable, the combined actions are sufficient to complete the task, and there is no local minimum in the search space. If these conditions hold, then a cooperative task can be accomplished without any communication between the contributing agents. However, for tasks that do contain local minima, the global solution can only be reached if at least one of the agents adapts its intention at the appropriate moments, and this can only be achieved by appropriately timed communication. In other words, it is hypothesised that in cooperative tasks, the function of communication is to coordinate actions in a complex search space that contains local minima. These principles have been verified in a computer-based simulation environment in which two independent one-dimensional agents are obliged to cooperate in order to solve a two-dimensional path-finding task.

翻译：人机交互领域的一个重要开放问题在于，智能体应在何时决定进行通信，尤其是在合作任务中。感知控制理论指出，智能体仅需共享相同的"意图"，即可通过分担完成任务所需的工作量来实现联合任务。即使智能体能力各异，只要目标可观测、联合行动足以完成任务，且搜索空间中不存在局部极小值，该结论依然成立。若这些条件满足，则合作任务可在贡献者之间无需任何通信的情况下完成。然而，对于存在局部极小值的任务，全球最优解仅能在至少一个智能体于适当时刻调整其意图时实现，而这唯有通过适时通信才能达成。换言之，我们假设：在合作任务中，通信的功能在于协调复杂搜索空间（包含局部极小值）中的行动。这些原理已在计算机仿真环境中得到验证——在该环境中，两个独立的一维智能体必须协作才能完成一项二维寻路任务。