Language Acquisition Environment for Human-Level Artificial Intelligence

Despite recent advances in many application-specific domains, we do not know how to build a human-level artificial intelligence (HLAI). We conjecture that learning from others' experience with the language is the essential characteristic that differentiates human intelligence from the rest. Humans can update the action-value function only with the verbal description as if they experience states, actions, and corresponding rewards sequences first hand. In this paper, we present our ongoing effort to build an environment to facilitate the research for models of this capability. In this environment, there are no explicit definitions of tasks or rewards given when accomplishing those tasks. Rather the models experience the experience of the human infants from fetus to 12 months. The agent should learn to speak the first words as a human child does. We expect the environment will contribute to the research for HLAI.