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Player Pressure Map -- A Novel Representation of Pressure in Soccer for Evaluating Player Performance in Different Game Contexts
We propose a player pressure map to represent a given game scene, which lowers the dimension of raw data and still contains rich contextual information.
Embedding Contextual Information through Reward Shaping in Multi-Agent Learning: A Case Study from Google Football
The experiment results in the GRF environment prove that our reward shaping method is a useful addition to state-of-the-art MARL algorithms for training agents in environments with sparse reward signal.
Deep Generative Multi-Agent Imitation Model as a Computational Benchmark for Evaluating Human Performance in Complex Interactive Tasks: A Case Study in Football
Then the trained Conditional VRNN Model is used as a benchmark to evaluate team performance.
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