Constructors
Properties
_epoch
_epoch: number
Accessors
epoch
- get epoch(): number
Returns number
reward
- set reward(value: any): void
Returns void
Methods
reset
- reset(): void
Returns void
sample_action
- sample_action(agent: any): any[]
Returns any[]
Sampled action
setState
- setState(state: any[], agent: any): void
Returns void
state
- state(agent: any): any[]
Returns any[]
Current state
step
- step(
action: any[],
agent: any,
): { done: boolean; invalid?: boolean; reward: number; state: any[] } Returns { done: boolean; invalid?: boolean; reward: number; state: any[] }
state, reward, done
test
- test(
state: any[],
action: any[],
agent: any,
): { done: boolean; invalid?: boolean; reward: number; state: any[] } Parameters
- state: any[]
- action: any[]
- agent: any
Returns { done: boolean; invalid?: boolean; reward: number; state: any[] }
state, reward, done
Base class for reinforcement learning environment