Scale-Adaptive Balancing of Exploration and Exploitation in Classical Planning

1. 1Apply Multi-Armed Bandit (MAB) literature to classical planning
2. 2Analyze the theoretical foundations of MAB to improve planning algorithms
3. 3Implement scale-adaptive balancing to optimize exploration and exploitation trade-offs
4. 4Evaluate the performance of the improved algorithms in various planning scenarios

AI engineers and researchers working on planning and decision-making algorithms can benefit from this research, as it provides a theoretical understanding of balancing exploration and exploitation

💡 Applying MAB literature to classical planning can improve algorithm performance

🤖 Scale-adaptive balancing for better planning!