"ML_AGENT POCA Training, One side learning well, other side bad" (346241)

Questions & Answers
1

Hi, I am trying to train competitive 2 vs 2 hockey game. It is symetrical game. I am using MA-POCA. My problem one of the teams learning very well but other side is very bad. How this can happen? MA-POCA algorthm using self-play and if one side is playing good, other team also should play well because it is using old policy. But this is not happening.

I also want to ask you one more thing. I add “footballer begining side” input which is 0 or 1. I do this because agent can start right sided or left sided so it should know which post he should score. Should I remove this king of input? Thanks for answers.

I check my team_id’s → They should be different so I arrange like that

I am sharing my config file

behaviors:
  SoccerAgent:
    trainer_type: poca
    hyperparameters:
      batch_size: 1024
      buffer_size: 10240
      learning_rate: 0.0003
      beta: 0.005
      epsilon: 0.2
      lambd: 0.95
      num_epoch: 3
      learning_rate_schedule: constant
    network_settings:
      normalize: false
      hidden_units: 512
      num_layers: 2
      vis_encode_type: simple
      goal_conditioning_type: none
    reward_signals:
      extrinsic:
        gamma: 0.99
        strength: 1.0
    keep_checkpoints: 5
    max_steps: 5000000
    time_horizon: 1024
    summary_freq: 20000
    self_play:
      save_steps: 100000
      team_change: 500000
      swap_steps: 10000
      window: 10
      play_against_latest_model_ratio: 0.5
      initial_elo: 1200.0