Base class for reinforcement learning environment

Hierarchy (View Summary)

Constructors

Properties

Accessors

Methods

Constructors

Properties

_epoch: number

Accessors

  • get epoch(): number
  • Epoch

    Returns number

  • set reward(value: any): void
  • Reward

    Parameters

    • value: any

      Reward object

    Returns void

Methods

  • Reset environment.

    Returns void

  • Sample an action.

    Parameters

    • agent: any

      Agent

    Returns any[]

    Sampled action

  • Set new state.

    Parameters

    • state: any[]

      New state

    • agent: any

      Agent

    Returns void

  • Returns current state.

    Parameters

    • agent: any

      Agent

    Returns any[]

    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

    • agent: any

      Agent

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

    state, reward, done