Added waste management solution using advanced reinforcement learning techniques #814
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👋 Thank you for opening this pull request! We appreciate your contribution to improving this project. Your PR is under review, and we'll get back to you shortly. To help move the process along, please tag @UppuluriKalyani, @Neilblaze, and @SaiNivedh26 for a faster review! |
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Nov 8, 2024
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🎉🎉 Thank you for your contribution! Your PR #814 has been merged! 🎉🎉 |
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Related Issues or bug
The project aims to develop a reinforcement learning (RL) agent to optimize waste collection in a simulated environment, minimizing overflow events and improving efficiency.
Fixes: #699
Proposed Changes
The epsilon-greedy strategy is a popular approach used in reinforcement learning to balance exploration and exploitation. The strategy employs a parameter, epsilon (ε), which determines the probability of choosing a random action (exploration) versus the best-known action (exploitation). As training progresses, epsilon typically decays, allowing the agent to rely more on learned knowledge and less on exploration.
Additional Info
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