کتاب کاربردهای پیشرفته یادگیری تقویتی چندعامله در اکتشاف فضایی و رباتیک ماه‌نورد با فرمت AZW3 برای کتابخوان کیندل و فرمت EPUB

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🎓 دوره آموزشی جامع

📚 اطلاعات دوره

عنوان دوره: دوره کاربردهای پیشرفته یادگیری تقویتی چندعامله در اکتشاف فضایی و رباتیک ماه‌نورد

موضوع کلی: یادگیری تقویتی چندعامله (MARL)

موضوع میانی: کاربردهای پیشرفته MARL

📋 سرفصل‌های دوره

  • 1. Introduction to Multi-Agent Reinforcement Learning
  • 2. Core concepts: agents, environments, rewards in MARL
  • 3. Comparison of single-agent vs multi-agent RL
  • 4. Overview of MARL algorithms: Q-learning, policy gradients
  • 5. Centralized training with decentralized execution (CTDE)
  • 6. Value-based MARL: VDN, QMIX
  • 7. Policy-based MARL: MADDPG, COMA
  • 8. Communication protocols in MARL
  • 9. Handling partial observability in multi-agent settings
  • 10. Exploration strategies for MARL
  • 11. Credit assignment problems and solutions
  • 12. Scalability challenges in large-scale MARL
  • 13. Simulation environments for space robotics (Gazebo, ROS, etc.)
  • 14. Modeling lunar terrain and lighting conditions
  • 15. Dynamics of lunar rovers and manipulators
  • 16. Sensor modeling: LIDAR, cameras, inertial units for MARL
  • 17. Safety constraints and risk-aware MARL
  • 18. Multi-objective MARL for mission success and resource conservation
  • 19. Hierarchical MARL for high-level task decomposition
  • 20. Curriculum learning for complex lunar missions
  • 21. Transfer learning from terrestrial to lunar MARL agents
  • 22. Domain adaptation techniques for varying lighting and dust
  • 23. Multi-agent path planning on lunar surface
  • 24. Cooperative localization and mapping (SLAM) with MARL
  • 25. Distributed decision-making for rover convoys
  • 26. Fault tolerance and recovery in MARL-driven rover teams
  • 27. Energy-aware MARL for power-limited lunar operations
  • 28. MARL for autonomous sample collection and analysis
  • 29. MARL-driven autonomous drilling and excavation
  • 30. Swarm robotics concepts applied to lunar exploration
  • 31. Emergent behaviors in MARL lunar swarms
  • 32. Communication latency and bandwidth constraints in MARL
  • 33. Using mesh networks for inter-rover communication
  • 34. Event-triggered communication to reduce bandwidth
  • 35. MARL for autonomous habitat construction
  • 36. MARL for in-situ resource utilization (ISRU) coordination
  • 37. MARL-driven dust mitigation strategies
  • 38. MARL for scientific experiment prioritization
  • 39. Real-time MARL with edge computing on rovers
  • 40. Low-latency inference optimization for MARL policies
  • 41. Hardware-in-the-loop testing of MARL lunar rovers
  • 42. Simulation-to-real (Sim2Real) transfer for lunar MARL
  • 43. Safety verification and validation of MARL policies
  • 44. Formal methods for verifying MARL lunar missions
  • 45. Ethical considerations and planetary protection in MARL
  • 46. MARL for autonomous navigation in permanently shadowed regions
  • 47. MARL for navigating crater rims and steep slopes
  • 48. MARL for teleoperation assistance and shared control
  • 49. MARL for autonomous rendezvous and docking of lunar landers
  • 50. MARL for coordinating orbiters and surface agents
  • 51. MARL for space debris avoidance near lunar orbit
  • 52. MARL for autonomous refueling and servicing missions
  • 53. MARL for multi-modal perception fusion (vision, LIDAR, thermal)
  • 54. MARL for adaptive locomotion (legged, wheeled, hybrid) on regolith
  • 55. MARL for learning locomotion policies from demonstration
  • 56. MARL for cooperative load carrying and manipulation
  • 57. MARL for autonomous assembly of lunar structures
  • 58. MARL for swarm-based seismic sensing networks
  • 59. MARL for monitoring and predicting lunar dust storms
  • 60. MARL for adaptive lighting compensation in imaging
  • 61. MARL for long-duration mission planning and replanning
  • 62. MARL for handling unexpected events (micrometeoroid impacts)
  • 63. MARL for autonomous scientific hypothesis generation
  • 64. MARL for multi-rover data fusion and decision making
  • 65. MARL for swarm-based antenna array deployment
  • 66. MARL for autonomous navigation using celestial navigation
  • 67. MARL for integrating with ground station scheduling
  • 68. MARL for fault detection and isolation (FDI) in rover subsystems
  • 69. MARL for adaptive communication power control
  • 70. MARL for end-to-end mission autonomy from launch to surface operations
تگ‌ها: AI for space missions autonomous agents cooperative control decentralized learning deep MARL hierarchical MARL lunar robotics lunar rover coordination MARL multi-agent systems path planning reinforcement learning simulation environments space exploration swarm intelligence

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