The paper presents a simple people-centric adaptive ecology between a humanoid robot and a virtual human (social agents) to perform a real-world common complex social task. The social task was to assist the social agents each other in searching for a hidden object in a homely environment. In order to develop the ecology between the agents, we developed the agents with various similar functionalities, interaction modalities, sensing abilities, intelligence, autonomy etc., and integrated them through a common communication platform based on a novel control algorithm. In order to assess people's acceptance of the ecology between the social agents and to benchmark the ecology, we studied human's interactions with those agents and with some other allied agents for that task.We evaluated the attributes and performances of the social agents in their cooperations for the task, analyzed the attributes and performances and benchmarked them with the standards. The results showed that both of the social agents within the ecology could perform satisfactorily to accomplish the common social task though the performances varied slightly between the agents.We also found a trade-off between the attributes and the performances of the social agents. We then proposed to use the results to develop adaptive social ecologies with intelligent social agents of different realities to assist the humans in various real-world complex social tasks in smart spaces, or to get the real-world social tasks done in cooperation between the social agents.