Collaborative tasks are ubiquitous activities where a form of communication is required in order to reach a joint goal. Collaborative building is one of such tasks. We wish to develop an intelligent builder agent in a simulated building environment (Minecraft) that can build whatever users wish to build by just talking to the agent. In order to achieve this goal, such agents need to be able to take the initiative by asking clarification questions when further information is needed. Existing works on Minecraft Corpus Dataset only learn to execute instructions neglecting the importance of asking for clarifications. In this paper, we extend the Minecraft Corpus Dataset by annotating all builder utterances into eight types, including clarification questions, and propose a new builder agent model capable of determining when to ask or execute instructions. Experimental results show that our model achieves state-of-the-art performance on the collaborative building task with a substantial improvement. We also define two new tasks, the learning to ask task and the joint learning task. The latter consists of solving both collaborating building and learning to ask tasks jointly.
翻译:合作性任务是无处不在的活动,为了达到共同的目标,需要有一种通信形式; 合作性建筑就是其中一项任务; 我们希望在模拟建筑环境中开发一个智能建筑剂(矿物),能够通过与代理人交谈来建立用户希望建造的任何设备; 为了实现这一目标,这些代理人需要能够在需要进一步的信息时通过询问澄清问题来采取主动; 地雷工艺公司数据库的现有工作只学会执行无视要求澄清重要性的指示; 在本文件中,我们通过说明所有建筑师的言论将采矿公司数据集扩展为8种类型,包括澄清问题,并提出能够确定何时询问或执行指示的新建筑剂模型; 实验结果显示,我们的模型在合作性建筑工作上取得最新业绩,并大大改进。 我们还确定了两项新任务,即学习要求任务和联合学习任务。 后者包括解决合作性建筑和学习共同要求任务。