A policy-gradient neural network can learn obstacle-avoiding target navigation in a continuous robosoccer domain, with partial transfer from static training to dynamic multi-agent evaluation.
A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles,
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Towards Learning Scalable Agile Dynamic Motion Planning for Robosoccer Teams with Policy Optimization
A policy-gradient neural network can learn obstacle-avoiding target navigation in a continuous robosoccer domain, with partial transfer from static training to dynamic multi-agent evaluation.