Coordination and cooperation between humans and autonomous agents in cooperative games raises interesting questions of human decision making and behaviour changes. Here we report our findings from a group formation game in a small-world network of different mixes of human and agent players, aiming to achieve connected clusters of the same colour by swapping places with neighbouring players using non-overlapping information. In the experiments the human players are incentivized by rewarding to prioritize their own cluster while the model of agents' decision making is derived from our previous experiment of purely cooperative game between human players. The experiments were performed by grouping the players in three different setups to investigate the overall effect of having cooperative autonomous agents within teams. We observe that the change in the behavior of human subjects adjusts to playing with autonomous agents by being less risk averse, while keeping the overall performance efficient by splitting the behaviour into selfish and cooperative in the two actions performed during the rounds of the game. Moreover, results from two hybrid human-agent setups suggest that the group composition affects the evolution of clusters. Our findings indicate that in purely or lesser cooperative settings, providing more control to humans could help in maximizing the overall performance of hybrid systems.
翻译:人类和自主者在合作游戏中的协调与合作提出了人类决策和行为变化的有趣问题。我们在这里报告我们从由不同人类和代理玩家混合组成的小世界网络中的组组装游戏中得出的调查结果,其目的是通过利用非重叠信息与相邻玩家交换位置,实现同颜色的相联集群。在实验中,人类玩家受到激励,通过奖励确定自己的组群的优先次序,而代理人的决策模式则来自我们以前在人类玩家之间纯粹合作游戏的实验。实验由三个不同的组合中的玩家进行,以调查在团队中拥有合作自主代理的总体效果。我们发现,人类主体行为的变化通过减少风险而适应与自主代理玩耍,同时通过将行为分成两轮游戏中的自私和合作行动来保持总体业绩的效率。此外,两个混合人类代理组合的结果表明,集团的组成会影响集群的演变。我们发现,在纯或较小的合作环境中,为人类提供更多的控制,可以帮助最大限度地发挥混合系统的整体性能。