Vain

Name: Vain
Start: 2024-08-30T18:00:00+07:00
Location: Whisky A Go GO

Schedule

Fri Aug 30 2024 at 06:00 pm

UTC+07:00

Location

Whisky A Go GO | Beverly Hills, CA

Multi-agent predictive modeling is an essential step for understanding physical, social and team-play systems. Recently, Interaction Networks (INs) were proposed for the task of modeling multi-agent physical systems, INs scale with the number of interactions in the system (typically quadratic or higher order in the number of agents). In this paper we introduce VAIN, a novel attentional architecture for multi-agent predictive modeling that scales linearly with the number of agents. We show that VAIN is effective for multi-agent predictive modeling. Our method is evaluated on tasks from challenging multi-agent prediction domains: chess and soccer, and outperforms competing multi-agent approaches.
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