For The Win: An AI Agent Achieves Human-Level Performance in a 3D Video Game

Author(s): Sherwin Chen

Originally published on Towards AI.

Environment Observation

Source: https://deepmind.com/blog/article/capture-the-flag-science

In this article, we’ll discuss For The Win(FTW) agent, from DeepMind, that achieves human-level performance in a popular 3D team-based multiplayer first-person video game. The FTW agent utilizes a novel two-tier optimization process in which a population of independent RL agents is trained concurrently from thousands of parallel matches with agents playing in teams together and against each other on randomly generated environments. Each agent in the population learns its internal reward signal to complement the sparse delayed reward from winning and selects actions using a novel temporally hierarchical representation that enables the agent to reason at multiple timescales.

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Published via Towards AI