Reinforcement learning to develop policies for fair and productive employment: A case study on wage theft within the day-laborer community
Fig 5
Game tree of the 2-player state space.
In the multiagent formulation, orange denotes the states where the employer makes the decisions and the actions that can be made, black lines represent the states where the day-laborer makes decisions and the actions they can take, and blue denotes the environment and the end results. The game is immediately replayed if the job does not begin and rewards are changed for both players in each state transition.