arXiv (OAI)
open access
Enhanced Deep Q-Learning for 2D Self-Driving Cars: Implementation and Evaluation on a Custom Track Environment
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Full-Trajectory Learning of Open Quantum Systems: Dynamical Emulation and the Limits of Hamiltonian Identifiability#1143883
- Physics-informed deep learning for robust trajectory prediction in automated driving / Anne Stockem Novo#814510
- Replay-buffer engineering for noise-aware quantum circuit optimization#1141525
- Urban traffic signal control optimization through Deep Q Learning and double Deep Q Learning: a novel approach for efficient traffic management.#489719
- Fuel Efficiency Prediction Using Deep Learning#105427
Record · ID 147000
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive