Learning optimal robotic tasks

摘要

A reinforcement learning system for machine-intelligence robots introduces a performance measure that balances an algorithm's reliability and computational cost. The system uses this measure to learn the best among a set of alternative tasks capable of executing a command communicated to the intelligent machine.