simple multi-agent gridworld gym loaded from text file maps with simple collision detection and prevention. This is the environment used for the gridworld environment in Safe multi-agent reinforcement learning via shielding.
- Step function:
- The reward for a collision can be set where
collision_cost
= -reward. If you want the reward of a collision to be -10 thencollision_cost=10
. - Penalty for unmoving agents can be set by having
noop=True
- The
share
variable should beTrue
for shared goals (ie. if multiple agents are going to one goal location). - Out of bounds checking with penalty -10.
- Random priority of agents for conflicting agent actions can be enabled with
random_priority=True
.
- The reward for a collision can be set where
Requires the OpenAI gym package.