I. Aim and Scope

Most of the current Reinforcement-Learning solutions, although having real-world-inspired scenarios, focus on a direct space-action-reward mapping between the agent's actions and the environment’s state. That translates to agents that can adapt to dynamic scenarios, but, when applied to competitive and/or cooperative cases, fail to assess and deal with the impact of their opponents. In most cases, when these agents choose an action, they do not take into consideration how other agents can affect the state of the scenario. In competitive scenarios, the agents have to learn decisions that a) maximize their chances of winning the game, and b) minimize their adversaries' goals, while in cooperative scenarios b) is inverted. Besides dealing with complex scenarios, such solutions would have to deal with the dynamics between the agents themselves. In this regard, social reinforcement learning is still behind the mainstream applications and demonstrations of the last years.

We introduce here the Chef's Hat Cup, a competition that aims at the development of the most challenging artificial players!

The competition is separated into two tracks: a competitive and a cooperative scenario. In the first track, the participants will use the already available simulation environment to develop the most effective agents to play the Chef’s Hat card game and be the winner. In the second track, they will have to develop an agent that can increase the chances of a dummy agent winning the game.

More information: https://www.whisperproject.eu/chefshat#competition

II. Deadlines

Starting Date: April 20, 2021

Final submission: June 15, 2021

Winners Announcement: July 06, 2021

III. Team Registration

Teams of up to five persons are invited to participate in the competition.

You can register by sending the following information:

Team name

Participant Names and affiliation

to this email: pablo.alvesdebarros@iit.it

IV. Organizers

Pablo Barros, Italian Institute of Technology (IIT), Italy

Leandro Honorato, University of Pernambuco, Brazil

Marco Matarese, Italian Institute of Technology (IIT), Italy

Alessandra Sciutti, Italian Institute of Technology (IIT), Italy