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Found 7 papers, 0 papers with code
Safety Aware Autonomous Path Planning Using Model Predictive Reinforcement Learning for Inland Waterways
We demonstrate our approach on two scenarios and compare the resulting path with path planning using a Frenet frame and path planning based on a proximal policy optimization (PPO) agent.
An In-Depth Analysis of Discretization Methods for Communication Learning using Backpropagation with Multi-Agent Reinforcement Learning
We do this comparison in the context of communication learning using gradients from other agents and perform tests on several environments.
Scalability of Message Encoding Techniques for Continuous Communication Learned with Multi-Agent Reinforcement Learning
Therefore, we analyse the communication protocol used by the agents that use the mean message encoder and can conclude that the agents use a combination of an exponential and a logarithmic function in their communication policy to avoid the loss of important information after applying the mean message encoder.
An Analysis of Discretization Methods for Communication Learning with Multi-Agent Reinforcement Learning
The most common approach to allow learned communication between agents is the use of a differentiable communication channel that allows gradients to flow between agents as a form of feedback.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
Learning to Communicate with Reinforcement Learning for an Adaptive Traffic Control System
In this paper, we investigate independent Q-learning (IQL) without communication and differentiable inter-agent learning (DIAL) with learned communication on an adaptive traffic control system (ATCS).
Mixed Cooperative-Competitive Communication Using Multi-Agent Reinforcement Learning
We look at the difference in performance between communication that is private for a team and communication that can be overheard by the other team.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
Learning to Communicate Using Counterfactual Reasoning
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.
