From Task Allocation to Risk Clearing: A Unifying Interface for Mixed Human-Agent Societies

2026-05-26

AI Summary

This work addresses the challenge of coordinating heterogeneous agents in safety-critical human–AI collaborative settings, where existing mechanisms struggle to simultaneously support dynamic task allocation, commitment under uncertainty, and scalable integration. The paper introduces Risk-aware Option Clearing (ROC), a novel coordination framework that treats risk-aware options as fundamental units of interaction. Each option encapsulates an agent’s temporally extended skill along with a concise risk summary. A central clearinghouse optimizes task assignment by jointly considering risk-adjusted utility, temporal deadlines, and safety constraints. The framework unifies diverse deployment paradigms—from data-driven learning to full distributional prediction—providing a transparent, interpretable, and scalable coordination infrastructure for mixed human–machine systems and advancing the applicability of risk-aware clearing layers in hybrid social environments.

Abstract

As humans, robots, and software agents increasingly share safety-critical environments, coordination must move from static task allocation to managing uncertain commitments. Existing frameworks fall short: they either assume rigid, static teams or learn opaque joint policies that are hard to adapt and difficult to integrate with human decision-makers. To overcome these limitations, we propose Risk-Aware Option Clearing (ROC), a unifying coordination mechanism in which agents expose options (temporally extended skills) paired with risk summaries that predict outcome distributions. A central clearinghouse then assigns tasks by optimizing risk-adjusted mission utility under deadlines and safety constraints. ROC is a family of mechanisms, ranging from deployments where the clearinghouse learns outcome models from data to ones that consume full distributional predictions from agents. By treating risk-aware options as the basic coordination unit, ROC sketches a scalable, transparent infrastructure for integrating heterogeneous agents into future mixed human--agent societies and outlines a research agenda for such risk-aware clearing layers.

Problem

• task allocation
• risk management
• human-agent coordination
• mixed societies
• uncertain commitments

Innovation

• Risk-Aware Coordination
• Option-Based Planning
• Clearinghouse Mechanism
• Mixed Human-Agent Societies
• Uncertain Commitments