Conflict resolution and bug fix#5
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…nd the target location are the same
tongyao129
commented
Feb 15, 2022
| print("{}: {}".format(drone_name, drone_info["WinningBids"])) | ||
| print("{}: {}".format(drone_name, drone_info["RawBids"])) | ||
| if np.sum(drone_info["TaskList"]) == 0: | ||
| availability = drone_info["TaskAvailability"] |
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availability after sum check
tongyao129
commented
Feb 15, 2022
| bid = (1 / (pos_diff)) | ||
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| if bid >= (drone_info["WinningBids"][i]): | ||
| if bid > (drone_info["WinningBids"][i]): |
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resolve conflict when bid are the same
tongyao129
commented
Feb 15, 2022
| for j, col in enumerate(bid_columns): | ||
| if debug: | ||
| print("Task {} Bids: {}".format(j + 1, col)) | ||
| best_bid = np.max(col) |
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when bids are the same as the previous best, do not change task assignment of agent
tongyao129
commented
Feb 15, 2022
| task_list[i] = 0 | ||
| for j, winner in enumerate(drone_info["Winners"]): | ||
| winner_id = winner["id"] | ||
| if winner_id != drone_id: |
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compare agent id instead of bid
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