Mag. Pablo Sauma Chacón

Mag. Pablo Sauma Chacón

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Operationalizing Intentionality to Play Hanabi with Human Players


The cooperative card game Hanabi has become of increasing interest in the community, since it combines partially hidden information with information exchange using restricted communication channels. In this paper, we describe AI agents that are designed to play the game with human players. Our agents make use of the fact that human players expect other players to act intentionally by formulating goals of their own and planning how to achieve them. They then use the available actions available to communicate their plan to the human player. On the flip side, our agents also interpret the actions performed by the human player as containing information about their plans. We present two different variants of our agent that perform this interpretation in different ways. Additionally, since part of human communication happens in subtle, indirect ways, we also demonstrate that our agent can use the timing of the human player's actions as additional information. In order to validate our agents, we have performed two separate experiments. One was done to validate the intentional component of the agents, while the other focused on the interpretation of received information. In this article, we also present the results obtained from these two experiments.

Tipo de publicación: Journal Article

Publicado en: IEEE Transactions on Games

Pandemic as a Challenge for Human-AI Cooperation


Cooperation between human players and AI agents in games is a subject of great interest in the research community. In this paper we propose a new domain as a challenge for future AI research: the cooperative game Pandemic. This game represents a challenge because it requires cooperation between players in an environment with incomplete information. Additionally, we propose a first approach for a cooperative agent for the game, that uses planning in conjunction with plan recognition. We also propose an experiment to test the mentioned approach. In this paper we argue why Pandemic makes a compelling domain for AI research, the status of our project, as well as which challenges remain to be addressed.

Tipo de publicación: Conference Paper

Publicado en: Sixteenth Artificial Intelligence and Interactive Digital Entertainment Conference