**Abstract**

The frequency of natural disasters is increasing everywhere in the world, which is a major impediment to sustainable development. One important issue for the international community is to reduce vulnerability to and damage from disasters. In addition, a large number of injuries occur simultaneously in a large-scale disaster, and the condition of the injured will change over time. Efficient rescue activities are carried out using triage to determine the priority of injury treatment based on the severity of the persons' conditions. In this chapter, we discuss acquiring cooperative behavior of rescuing the injured and clearing obstacles according to triage of the injured in a multi-agent system. We propose three methods of reward distribution: (1) reward distribution responding to the condition of the injured, (2) reward distribution based on the contribution degree, and (3) reward distribution by the contribution degree responding to the condition of the injured. We investigated the effectiveness of the three proposed methods for a disaster relief problem by an experiment. The results of the experiment showed that agents gained high rewards by rescuing those in most urgent need under the method having the reward distributed according to the contribution degree responding to the condition of the injured.

**Keywords:** multi-agent system, reinforcement learning, reward distribution, triage, disaster relief problem
