Every Team Deserves a Second Chance: An Interactive 9x9 Go Experience (Demonstration)

We show that without using any domain knowledge, we can predict the final performance of a team of voting agents, at any step towards solving a complex problem. This demo allows users to interact with our system, and observe its predictions, while playing 9x9 Go. Categories and Subject Descriptors I.2.1 [Artificial Intelligence]: Applications and Expert Systems Keywords Teamwork; Single and multiagent learning; Social choice

• Type: Journal
• Year: 2015
• Where: ATAL
• Authors: Leandro Soriano Marcolino, Vaishnavh Nagarajan, Milind Tambe
• Keywords: ATAL 2015, Intelligent Agents