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Handling Collisions with Limited 3x3 FOV #3
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Hello! |
Thank you for your detailed response. I am particularly intrigued by the specifics of the communication and tie-breaking mechanisms in SCRIMP, especially within a decentralized framework. Could you provide more details on the type of information exchanged between agents during these phases? Additionally, is the communication process based on multiple rounds, or does it utilize a global information channel? On another note, I recommend exploring lookahead techniques like Monte Carlo Tree Search to further refine the tie-breaking strategy. Our recent paper https://arxiv.org/pdf/2312.15908.pdf delves into similar methodologies and might provide some valuable insights for your research. |
Hello author,when installing modules according to txt in readme, networkx2.8.8 is inconsistent with python3.7. How can I solve it? Thank you |
Hello!
First off, thank you for your work on the SCRIMP paper. It presents an intriguing approach to the challenges problem.
One aspect I'm curious about is how SCRIMP handles potential collisions with a very restricted 3x3 FOV. To paint a picture, consider a scenario where two agents (agents A [moving right] and B [moving left]) are in a narrow corridor with just a single cell between them, such that they're outside each other's FOVs:
Given their limited visibility, how does the system ensure these agents avoid collisions in real-time? Does the global communication mechanism based on the modified transformer help in such close-quartered scenarios, or are there other components of the system that play a role in avoiding potential conflicts in such situations?
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