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Found 9 papers, 4 papers with code
AgentStudio: A Toolkit for Building General Virtual Agents
We have open-sourced the environments, datasets, benchmarks, and interfaces to promote research towards developing general virtual agents for the future.
AdaRec: Adaptive Sequential Recommendation for Reinforcing Long-term User Engagement
One challenge in large-scale online recommendation systems is the constant and complicated changes in users' behavior patterns, such as interaction rates and retention tendencies.
A Large Language Model Enhanced Conversational Recommender System
For response generation, we utilize the generation ability of LLM as a language interface to better interact with users.
State Regularized Policy Optimization on Data with Dynamics Shift
Data with dynamics shift are separated according to their environment parameters to train the corresponding policy.
Guarded Policy Optimization with Imperfect Online Demonstrations
Assuming optimal, the teacher policy has the perfect timing and capability to intervene in the learning process of the student agent, providing safety guarantee and exploration guidance.
Two-Stage Constrained Actor-Critic for Short Video Recommendation
One the one hand, the platforms aims at optimizing the users' cumulative watch time (main goal) in long term, which can be effectively optimized by Reinforcement Learning.
PrefRec: Recommender Systems with Human Preferences for Reinforcing Long-term User Engagement
Though promising, the application of RL heavily relies on well-designed rewards, but designing rewards related to long-term user engagement is quite difficult.
MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement Learning
Based on MetaDrive, we construct a variety of RL tasks and baselines in both single-agent and multi-agent settings, including benchmarking generalizability across unseen scenes, safe exploration, and learning multi-agent traffic.
Regret Minimization Experience Replay in Off-Policy Reinforcement Learning
In reinforcement learning, experience replay stores past samples for further reuse.
