### Body

There are some use cases where users want to trigger new DAG run as soon as one finished. This is a request I've seen several times with some variations (for example like this [Stackoverflow question](https://stackoverflow.com/q/75623153/14624409)) but the basic request is the same.

The workaround users do to get such functionality is place `TriggerDagRunOperator` as last task of their DAG invoking the same DAG:

```
from datetime import datetime

from airflow import DAG
from airflow.operators.empty import EmptyOperator
from airflow.operators.trigger_dagrun import TriggerDagRunOperator

with DAG(
    dag_id="example",
    start_date=datetime(2023, 1, 1,),
    catchup=False,
    schedule=None,
) as dag:
    task = EmptyOperator(task_id="first")
    trigger = TriggerDagRunOperator(
        task_id="trigger",
        trigger_dag_id="example",
    )

    task >> trigger

```

As you can see this works nicely:
![Screenshot 2023-03-03 at 14 20 51](https://user-images.githubusercontent.com/45845474/222718862-dfde8a41-24b6-4991-b318-b7f9784514f6.png)

My suggestion is to add first class support for this use case, so the above example will be changed to:

```

from datetime import datetime

from airflow import DAG
from airflow.operators.empty import EmptyOperator
from airflow.operators.trigger_dagrun import TriggerDagRunOperator

with DAG(
    dag_id="example",
    start_date=datetime(2023, 1, 1,),
    catchup=False,
    schedule="@continues",
) as dag:
    task = EmptyOperator(task_id="first")
```

I guess it won't exactly be `"@continues"` but more likely new [ScheduleArg](https://github.com/apache/airflow/blob/8b8552f5c4111fe0732067d7af06aa5285498a79/airflow/models/dag.py#L127) type but I show it like that just for simplification of the idea.

### Committer

- [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.
"Setting next_dagrun for %s to %s, run_after=%s",
            dag.dag_id,
            self.next_dagrun,
            self.next_dagrun_create_after,
        )
    @provide_session
    def get_dataset_triggered_next_run_info(self, *, session=NEW_SESSION) -> dict[str, int | str] | None:
        if self.schedule_interval != "Dataset":
            return None
        return get_dataset_triggered_next_run_info([self.dag_id], session=session)[self.dag_id]
def dag(
    dag_id: str = "",
    description: str | None = None,
    schedule: ScheduleArg = NOTSET,
    schedule_interval: ScheduleIntervalArg = NOTSET,
    timetable: Timetable | None = None,
    start_date: datetime | None = None,
    end_date: datetime | None = None,
    full_filepath: str | None = None,
    template_searchpath: str | Iterable[str] | None = None,
    template_undefined: type[jinja2.StrictUndefined] = jinja2.StrictUndefined,
    user_defined_macros: dict | None = None,
    user_defined_filters: dict | None = None,
    default_args: dict | None = None,
    concurrency: int | None = None,
    max_active_tasks: int = conf.getint("core", "max_active_tasks_per_dag"),
    max_active_runs: int = conf.getint("core", "max_active_runs_per_dag"),
    dagrun_timeout: timedelta | None = None,
    sla_miss_callback: None | SLAMissCallback | list[SLAMissCallback] = None,
    default_view: str = conf.get_mandatory_value("webserver", "dag_default_view").lower(),