This interactive visualization shows how a deep reinforcement learning agent’s performance evolves over training timesteps, with multiple score series tracking different agents or runs. The chart animates through the training timeline, allowing viewers to compare score trajectories and observe how performance improves over time. Built with D3.js v7, the SVG-based visualization uses a slider to scrub through timesteps and dynamically update the line chart. The data comes from a hardcoded score list, and the page includes tabbed navigation and buttons to switch between overview and detailed views of the training process.