Agents
No Free Lunch Theorem and Black-Box Complexity Analysis for Adversarial Optimisation
Black-box optimisation is one of the important areas in optimisation.
Federated Natural Policy Gradient and Actor Critic Methods for Multi-task Reinforcement Learning Tong Y ang
We further propose a federated natural actor critic (NAC) method for multi-task RL with function approximation and stochastic policy evaluation, and establish its finite-time sample complexity taking the errors of function approximation into account.
Human-Aware Vision-and-Language Navigation: Bridging Simulation to Reality with Dynamic Human Interactions Heng Li
Vision-and-Language Navigation (VLN) aims to develop embodied agents that navigate based on human instructions. However, current VLN frameworks often rely on static environments and optimal expert supervision, limiting their real-world applicability. To address this, we introduce Human-Aware Vision-and-Language Navigation (HA-VLN), extending traditional VLN by incorporating dynamic human activities and relaxing key assumptions.
Multi-Agent Coordination via Multi-Level Communication
SeqComm are guaranteed to improve monotonically and converge.
