all AI news
Learning to Communicate Using Counterfactual Reasoning. (arXiv:2006.07200v3 [cs.LG] UPDATED)
April 13, 2022, 1:12 a.m. | Simon Vanneste, Astrid Vanneste, Kevin Mets, Ali Anwar, Siegfried Mercelis, Steven Latré, Peter Hellinckx
cs.LG updates on arXiv.org arxiv.org
Learning to communicate in order to share state information is an active
problem in the area of multi-agent reinforcement learning (MARL). The credit
assignment problem, the non-stationarity of the communication environment and
the creation of influenceable agents are major challenges within this research
field which need to be overcome in order to learn a valid communication
protocol. This paper introduces the novel multi-agent counterfactual
communication learning (MACC) method which adapts counterfactual reasoning in
order to overcome the credit assignment problem …
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
Senior ML Researcher - 3D Geometry Processing | 3D Shape Generation | 3D Mesh Data
@ Promaton | Europe
Senior AI Engineer, EdTech (Remote)
@ Lightci | Toronto, Ontario
Data Scientist for Salesforce Applications
@ ManTech | 781G - Customer Site,San Antonio,TX
AI Research Scientist
@ Gridmatic | Cupertino, CA
Data Engineer
@ Global Atlantic Financial Group | Boston, Massachusetts, United States
Machine Learning Engineer - Conversation AI
@ DoorDash | Sunnyvale, CA; San Francisco, CA; Seattle, WA; Los Angeles, CA