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US 2019/0378042 A1Published application
Pre-Training of a Reinforcement Learning Ground Vehicle Controller Using Monte Carlo Simulation
AssigneeTraxen Inc.
InventorsGerti TUZI, Saeed ZAMANZAD GAVIDEL, Syed ALI, Ali MALEKI
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Abstract
Techniques for utilizing a Monte Carlo model to perform pre-training of a ground vehicle controller. A sampled distribution of actions and corresponding states can be utilized to train a reinforcement learning controller policy, learn an action-value function, or select a set of control parameters with a predetermined loss.
Claims21
A method comprising:
- receiving a Monte Carlo generated stochastic control model of a set of ground vehicle drivers;
- generating training data by sampling actions for given states of the Monte Carlo generated stochastic control model in a simulated ground vehicle environment and collecting traces of sequences of states, actions and rewards;
- pre-training using the training data including the collected traces of sequences of states, actions, and rewards to learn a stochastic value function for expected discounted future returns;
- and
- training a reinforcement learning controller using the stochastic value function.
2 more elements
A method comprising:
- receiving a stochastic Monte Carlo inferred model of a set of ground vehicle drivers;
- generating training data by sampling actions for given states of the stochastic Monte Carlo model in a simulated ground vehicle environment and collecting traces of sequences of states and probabilities of actions;
- pre-training using the training data including the collected traces of sequences of states and probability of action to generate a stochastic policy;
- and
- training a reinforcement learning controller using the stochastic policy.
2 more elements
Dependencies are inferred from the claim text.