RLUC: Strengthening robustness by attaching constraint considerations to policy network
J Tang, Q Liu, F Li, F Zhu - Expert Systems with Applications, 2024 - Elsevier
Deep reinforcement learning is widely used in many fields. However, recent research has
found vulnerabilities in agents trained by reinforcement learning algorithms and raised …
found vulnerabilities in agents trained by reinforcement learning algorithms and raised …
Self-adaptive imitation learning: Learning tasks with delayed rewards from sub-optimal demonstrations
Reinforcement learning (RL) has demonstrated its superiority in solving sequential decision-
making problems. However, heavy dependence on immediate reward feedback impedes …
making problems. However, heavy dependence on immediate reward feedback impedes …
Situation-Dependent Causal Influence-Based Cooperative Multi-Agent Reinforcement Learning
Learning to collaborate has witnessed significant progress in multi-agent reinforcement
learning (MARL). However, promoting coordination among agents and enhancing …
learning (MARL). However, promoting coordination among agents and enhancing …
Phoebe: Reuse-aware online caching with reinforcement learning for emerging storage models
With data durability, high access speed, low power efficiency and byte addressability, NVMe
and SSD, which are acknowledged representatives of emerging storage technologies, have …
and SSD, which are acknowledged representatives of emerging storage technologies, have …
A Simple Way to Incorporate Novelty Detection in World Models
G Zollicoffer, K Eaton, J Balloch, J Kim… - arxiv preprint arxiv …, 2023 - arxiv.org
Reinforcement learning (RL) using world models has found significant recent successes.
However, when a sudden change to world mechanics or properties occurs then agent …
However, when a sudden change to world mechanics or properties occurs then agent …
A novel mountain driving unity simulated environment for autonomous vehicles
The simulated driving environment provides a low cost and time-saving platform to test the
performance of the autonomous vehicle by linkage with existing machine learning …
performance of the autonomous vehicle by linkage with existing machine learning …
User-oriented robust reinforcement learning
Recently, improving the robustness of policies across different environments attracts
increasing attention in the reinforcement learning (RL) community. Existing robust RL …
increasing attention in the reinforcement learning (RL) community. Existing robust RL …