Check details in Jidi Competition IJCAI-ECAI 2022 AI Qlympics Competition

TagsPartial Observation; Continuous Action Space; Continuous Observation Space

Introduction: Agents participate in the Olympic Games. In this series of competitions, two agents participate in different Olympics games, including running, football, table hockey, wrestling etc.

Environment Rules:

1. This game has two sides and both sides control an elastic ball agent with the same mass and radius.
2. Agents can collide with each other or walls, but they might lose a certain speed. The agent has its own energy, and the energy consumed in each step is directly proportional to the applied driving force and displacement.
3. The energy of the agent recovers at a fixed rate at the same time. If the energy decays to zero, the agent will be tired, resulting in failure to apply force.
4. The whole game contains the subgames below. In running, the goal is to reach the end as fast as possible. In football, agent needs to hit the ball through collision into opponent's goal and defend his own goal. In table-hockey, agents share the same objective as in football except that they can only move freely in our own half court. In wrestling, agent who knock others out of bounds while keeping staying in bounds wins the game.
5. The game ends when all subgames are finished.

Action Space: Continuous, a matrix with shape 2*1, representing applied force and steering angle respectively.

Observation: A dictionary with keys 'obs' and 'controlled_player_index'. The value of 'obs' contains a 2D matrix with shape of 40x40 and other game-releated infomation. The 2D matrix records the view of agent along his current direction. Agent can see walls, marking lines, opponents and other game object within the vision area. The value of 'controlled_player_index' is the player id of the game.

Reward: Each team obtains a +1 reward when winning a subgame, and 0 reward when losing a subgame.

Environment ends condition: The game ends when all subgames are finished.

Registration: Go to (http://www.jidiai.cn/compete_detail?compete=17).

This is a POMDP simulated environment of 2D sports games where althletes are spheres and have continuous action space (torque and steering). The observation is a 30*30 array of agent's limited view range. We introduce collision and agent's fatigue such that no torque applies when running out of energy.

This is for now a beta version and we intend to add more sports scenario, stay tuned :)

conda create -n olympics python=3.8.5

conda activate olympics

pip install -r requirements.txt

python olympics_engine/main.py

You can locally test your submission. At Jidi platform, we evaluate your submission as same as run_log.py

For example,

python run_log.py --my_ai "random" --opponent "random"

in which you are controlling agent 1 which is green.

Random policy --> agents/random/submission.py