Local Minima Drive Communications in Cooperative Interaction
Roger K. Moore

TL;DR
This paper explores how local minima in search spaces influence when agents should communicate in cooperative human-robot interactions, emphasizing the role of communication in navigating complex search landscapes.
Contribution
It introduces a theoretical framework linking local minima to communication timing in cooperative tasks, validated through computer simulations with agents solving path-finding problems.
Findings
Communication is essential at local minima to reach global solutions.
Agents can cooperate without communication if no local minima exist.
Timing of communication is crucial for overcoming local minima in complex tasks.
Abstract
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…
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Taxonomy
TopicsDistributed Control Multi-Agent Systems
