Improving Policies via Search in Cooperative Partially Observable Games

Understand

Recent superhuman results in games have largely been achieved in a variety of zero-sum settings, such as Go and Poker, in which agents need to compete against others.

• However, just like humans, real-world AI systems have to coordinate and communicate with other agents in cooperative partially observable environments as well.
• These settings commonly require participants to both interpret the actions of others and to act in a way that is informative when being interpreted.
• Those abilities are typically summarized as theory f mind and are seen as crucial for social interactions.