@ai-on-browser/data-analysis-models
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    Class MountainCarRLEnvironment

    MountainCar environment

    Hierarchy (View Summary)

    Index

    Constructors

    Properties

    _epoch: number
    _force: number
    _g: number
    _goal_position: number
    _goal_velocity: number
    _max_position: number
    _max_step: number
    _max_velocity: number
    _min_position: number
    _position: number
    _reward: { fail: number; goal: number; step: number }
    _velocity: number

    Accessors

    • get actions(): number[][]

      Returns number[][]

    • get epoch(): number

      Epoch

      Returns number

    • set reward(value: object): void

      Reward

      Parameters

      • value: object

        Reward object

      Returns void

    Methods

    • Reset environment.

      Returns number[]

    • Sample an action.

      Parameters

      • agent: any

        Agent

      Returns any[]

      Sampled action

    • Set new state.

      Parameters

      • state: any

        New state

      Returns void

    • Returns current state.

      Returns number[]

      Current state

    • Do action and returns new state.

      Parameters

      • action: any[]

        Actions to be performed by the agent

      • agent: any

        Agent

      Returns { done: boolean; invalid?: boolean; reward: number; state: any[] }

      state, reward, done

    • Do actioin without changing environment and returns new state.

      Parameters

      • state: any

        Environment state

      • action: any

        Actions to be performed by the agent

      Returns { done: boolean; reward: number; state: any[] }

      state, reward, done