Due to the advent of deep RL methods that allow the study of many agents in rich environments, multi-agent reinforcement learning has flourished in recent years. However, most of this work considers fully cooperative settings (Omidshafiei et al., 2017; Foerster et al., 2017a,b) and emergent communication in particular (Das et al., 2017; Mordatch and Abbeel, 2017; Lazaridou, Peysakhovich, and Baroni, 2016; Foerster et al., 2016; Sukhbaatar, Fergus, and others, 2016). Considering future applications of multi-agent RL, such as self-driving cars, it is obvious that many of these will be yEqual Contribution only partially cooperative and contain elements of competition and selfish incentives

1709.04326.pdf

• We are an exchange download platform that only provides communication channels. The downloaded content comes from the internet. Except for download issues, please Google on your own.
• The downloaded content is provided for members to upload. If it unintentionally infringes on your copyright, please contact us.
• Please use Winrar for decompression tools
• If download fail, Try it againg or Feedback to us.
• If downloaded content did not match the introduction, Feedback to us，Confirm and will be refund.
• Before downloading, you can inquire through the uploaded person information

Nothing．