Search Results for author:
Found 5 papers, 0 papers with code
LLM-Personalize: Aligning LLM Planners with Human Preferences via Reinforced Self-Training for Housekeeping Robots
We introduce LLM-Personalize, a novel framework with an optimization pipeline designed to personalize LLM planners for household robotics.
Multiagent Model-based Credit Assignment for Continuous Control
By formulating robotic components as a system of decentralised agents, this work presents a decentralised multiagent reinforcement learning framework for continuous control.
Option Transfer and SMDP Abstraction with Successor Features
Abstraction plays an important role in the generalisation of knowledge and skills and is key to sample efficient learning.
Replication-Robust Payoff-Allocation for Machine Learning Data Markets
In this paper, we systematically study the replication manipulation in submodular games and investigate replication robustness, a metric that quantitatively measures the robustness of solution concepts against replication.
Multi-agent Hierarchical Reinforcement Learning with Dynamic Termination
We evaluate our model empirically on a set of multi-agent pursuit and taxi tasks, and show that our agents learn to adapt flexibly across scenarios that require different termination behaviours.
Hierarchical Reinforcement Learning
reinforcement-learning
+1
