Agents
A Unified Interface to Multiple Human Trajectory
Research in trajectory forecasting (i.e., predicting where an agent will be in the future) has grown
Information Design in Multi-Agent Reinforcement Learning
To thrive in those environments, the agent needs to influence other agents so their actions become more helpful and less harmful. Research in computational economics distills two ways to influence others directly: by providing tangible goods ( mechanism design) and by providing information ( information design). This work investigates information design problems for a group of RL agents. The main challenges are two-fold. One is the information provided will immediately affect the transition of the agent trajectories, which introduces additional non-stationarity. The other is the information can be ignored, so the sender must provide information that the receiver is willing to respect.
Information Design in Multi-Agent Reinforcement Learning
To thrive in those environments, the agent needs to influence other agents so their actions become more helpful and less harmful. Research in computational economics distills two ways to influence others directly: by providing tangible goods ( mechanism design) and by providing information ( information design). This work investigates information design problems for a group of RL agents. The main challenges are two-fold. One is the information provided will immediately affect the transition of the agent trajectories, which introduces additional non-stationarity. The other is the information can be ignored, so the sender must provide information that the receiver is willing to respect.
Asynchronous Proportional Response Dynamics: Convergence in Markets with Adversarial Scheduling
Almost all works that study market dynamics consider synchronous dynamics.
How2comm: Communication-Efficient and Collaboration-Pragmatic Multi-Agent Perception Dingkang Y ang 1,2 Kun Y ang 1 Y uzheng Wang
Our novelties lie in three aspects.
4b0eea69deea512c9e2c469187643dc2-Paper-Conference.pdf
Ta s k: Your task is to boil tin.
AT oolkit for Reliable Benchmarking and Research in Multi-Objective Reinforcement Learning
There are several reasons why reproducibility is often a challenge in RL.
Diverse Conventions for Human-AI Collaboration
Players have to manage the ingredients, use the stove, and deliver meals. As the team works together, they decide how tasks should be allocated among themselves so resources are used effectively. For example, player 1 could notice that player 2 tends to stay near the stove, so they instead spend more time preparing ingredients and delivering food, allowing player 2 to continue working at the stove. Through these interactions, the team creates a "convention" in the