DARPA ULTRALOG Final Report - Industrial and Manufacturing ...

Extensive testing and validation of the algorithms
was performed on a number of societies with varying
number of agents. The results obtained with the linear
estimator approach seem very encouraging across
different supply classes. Due to space limitations we
would show results for few of these items 1 . Figure 5
shows actual demand and predicted demand values for
an Ammunition item. We can see that the predicted
values are very close to the actual values and match with
the reorder periods of the actual demand. The
communications were cut for 12 days (day 43 -55)
during which we can still see the predictions, but no
actual demand tasks. In Figure 6 (for Subsistence item)
observe that the predicted demand catches up with the
actual demand. The initial error is due to the initial
model inaccuracies that are reduced as the model is
updated with observed data.
Figure 6. Actual vs. Predicted values for
Subsistence item
Figure 5. Actual vs. Predicted values for Ammo
item
Figure 7 and Figure 8 show the planned demand
(model), actual demand, predicted demand without
communication loss and predicted demand with
communication loss for BulkPOL item and Subsistence
item respectively. As actual demand values roll in, the
measurement equations reduce the error causing the
model to closely mimic the actual demand pattern. With
communication loss, the predictor uses the last updated
value to forecast demand.
Figure 7. With & W/o Comm. Loss Prediction
for BulkPOL item
1 Some of the experimental results in this paper are shown for Tiny
and Small societies, which are smaller versions of Full society. Note
that since the agents are generic, the demand patterns are similar in all
the societies.
Figure 8. With & W/o Comm. Loss Prediction
for Subsistence item