Trustworthy AI
Machine Learning
A policy optimization algorithm that guarantees monotonic improvement by constraining policy updates.
Detailed Explanation
Trust Region Policy Optimization (TRPO) is a reinforcement learning algorithm designed to improve policy stability by limiting the size of policy updates within a "trust region." This constraint ensures each update results in a monotonic (consistent) performance improvement, preventing drastic changes that could degrade learning. TRPO balances exploration and exploitation, leading to more reliable and efficient policy optimization.
Use Cases
- •Enhancing robot navigation stability through reliable policy updates that prevent drastic changes during reinforcement learning.
Related Terms
Other terms in the Machine Learning category