Shivansh Beohar
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View article: Planning with RL and episodic-memory behavioral priors
Planning with RL and episodic-memory behavioral priors Open
The practical application of learning agents requires sample efficient and interpretable algorithms. Learning from behavioral priors is a promising way to bootstrap agents with a better-than-random exploration policy or a safe-guard agains…
View article: Solving Learn-to-Race Autonomous Racing Challenge by Planning in Latent Space
Solving Learn-to-Race Autonomous Racing Challenge by Planning in Latent Space Open
Learn-to-Race Autonomous Racing Virtual Challenge hosted on wwwaicrowdcom platform consisted of two tracks: Single and Multi Camera. Our UniTeam team was among the final winners in the Single Camera track. The agent is required to pass the…