Figure 5 - available via license: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
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Example Boid results of our method. The configurations are the same as Fig. 4. The numbers are the start of the long-term prediction (trajectories). The "a" in the lower caption is the intervention times.
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Evaluation of intervention in a multi-agent system, e.g., when humans should intervene in autonomous driving systems and when a player should pass to teammates for a good shot, is challenging in various engineering and scientific fields. Estimating the individual treatment effect (ITE) using counterfactual long-term prediction is practical to evalu...
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... VRNN is the best performing model. On average, the ITE values were 0.059 ± 0.010 (km) in our best model (TG-CRN), 0.026 ± 0.001 in the baseline (GCRN+X), and 0.091±0.026 in the ground truth. From this viewpoint (both average and variance), our best model was closer to the ground truth than the baseline. Example results of our method are shown in Fig. 5. Our best model (TG-CRN) shows better counterfactual covariate prediction with intervention than the baseline (GCRN+X). Moreover, the counterfactual prediction of the outcome in our model had variation among various intervention times, whereas that in the baseline did not. We consider that these were important ...
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Evaluation of intervention in a multiagent system, for example, when humans should intervene in autonomous driving systems and when a player should pass to teammates for a good shot, is challenging in various engineering and scientific fields. Estimating the individual treatment effect (ITE) using counterfactual long-term prediction is practical to...
We propose a multi-agent system that enables groups of agents to collaborate and work autonomously to execute tasks. Groups can work in a decentralized manner and can adapt to dynamic changes in the environment. Groups of agents solve assigned tasks by exploring the solution space cooperatively based on the highest reward first. The tasks have a de...
