A survey of temporal credit assignment in deep reinforcement learning
The Credit Assignment Problem (CAP) refers to the longstanding challenge of
Reinforcement Learning (RL) agents to associate actions with their long-term …
Reinforcement Learning (RL) agents to associate actions with their long-term …
Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning
When decisions are made at high frequency, traditional reinforcement learning (RL)
methods struggle to accurately estimate action values. In turn, their performance is …
methods struggle to accurately estimate action values. In turn, their performance is …
Assessing the Zero-Shot Capabilities of LLMs for Action Evaluation in RL
The temporal credit assignment problem is a central challenge in Reinforcement Learning
(RL), concerned with attributing the appropriate influence to each actions in a trajectory for …
(RL), concerned with attributing the appropriate influence to each actions in a trajectory for …
Improving llm generation with inverse and forward alignment: Reward modeling, prompting, fine-tuning, and inference-time optimization
Large Language Models (LLMs) are often characterized as samplers or generators in the
literature, yet maximizing their capabilities in these roles is a complex challenge. Previous …
literature, yet maximizing their capabilities in these roles is a complex challenge. Previous …
Credit Assignment in Deep Reinforcement Learning
T Mesnard - 2023 - theses.hal.science
Deep reinforcement learning has been at the heart of many revolutionary results in artificial
intelligence in the last few years. These agents are based on credit assignment techniques …
intelligence in the last few years. These agents are based on credit assignment techniques …