Learning to Execute Actions or Ask Clarification Questions

Abstract

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.

Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos

“…Minecraft is a voxel-based 3D video game that, due its popularity and wide variety of mechanics, has attracted a vast amount of RL research. 27,28,[30][31][32][33][34][52][53][54][55][56][57][58][59][60] A large body of work focuses on small, custom-made Minecraft worlds with tasks such as navigation, 53,60 block placing, 54,55 instruction following, 58,59 combat, 56 and others. 28,31,57 Work operating in the massive, randomly generated environments of Minecraft itself has included hill climbing, 52 automated curriculum learning 30 and, most closely related to the RL experiments presented in Sec.…”