Human-AI Collaboration in Real-World Complex Environment with Reinforcement Learning

no code implementations • 23 Dec 2023 • Md Saiful Islam, Srijita Das, Sai Krishna Gottipati, William Duguay, Clodéric Mars, Jalal Arabneydi, Antoine Fagette, Matthew Guzdial, Matthew-E-Taylor

In this work, we show that learning from humans is effective and that human-AI collaboration outperforms human-controlled and fully autonomous AI agents in a complex simulation environment.

reinforcement-learning Reinforcement Learning (RL)

Receding Horizon Control in Deep Structured Teams: A Provably Tractable Large-Scale Approach with Application to Swarm Robotics

no code implementations • 20 Oct 2021 • Jalal Arabneydi, Amir G. Aghdam

The problem is formulated as a linear quadratic deep structured team, where the decision-makers wish to track a global target cooperatively while considering their local targets.

Reinforcement Learning in Linear Quadratic Deep Structured Teams: Global Convergence of Policy Gradient Methods

no code implementations • 29 Nov 2020 • Vida Fathi, Jalal Arabneydi, Amir G. Aghdam

In such systems, agents are partitioned into a few sub-populations wherein the agents in each sub-population are coupled in the dynamics and cost function through a set of linear regressions of the states and actions of all agents.

Policy Gradient Methods