### 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.
"""
        Returns edge information for the given pair of tasks if present, and
        an empty edge if there is no information.
        """
        
        empty = cast(EdgeInfoType, {})
        if self.edge_info:
            return self.edge_info.get(upstream_task_id, {}).get(downstream_task_id, empty)
        else:
            return empty
    def set_edge_info(self, upstream_task_id: str, downstream_task_id: str, info: EdgeInfoType):
        """
        Sets the given edge information on the DAG. Note that this will overwrite,
        rather than merge with, existing info.
        """
        self.edge_info.setdefault(upstream_task_id, {})[downstream_task_id] = info
    def validate_schedule_and_params(self):
        """
        Validates & raise exception if there are any Params in the DAG which neither have a default value nor
        have the null in schema['type'] list, but the DAG have a schedule_interval which is not None.
        """
        if not self.timetable.can_run:
            return
        for k, v in self.params.items():
            
            if not v.has_value and ("type" not in v.schema or "null" not in v.schema["type"]):
                raise AirflowException(
                    "DAG Schedule must be None, if there are any required params without default values"
                )
    def iter_invalid_owner_links(self) -> Iterator[tuple[str, str]]: