Search Results for author:
Found 3 papers, 2 papers with code
Towards optimized actions in critical situations of soccer games with deep reinforcement learning
For instance, in the optimized policy, we observe that some actions such as foul, or ball out can be sometimes more rewarding than a shot in specific situations.
AttendLight: Universal Attention-Based Reinforcement Learning Model for Traffic Signal Control
The first attention model is introduced to handle different numbers of roads-lanes; and the second attention model is intended for enabling decision-making with any number of phases in an intersection.
Reinforcement Learning for Solving the Vehicle Routing Problem
Our model represents a parameterized stochastic policy, and by applying a policy gradient algorithm to optimize its parameters, the trained model produces the solution as a sequence of consecutive actions in real time, without the need to re-train for every new problem instance.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
