### 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.
dag = models.DAG("dummy-dag", schedule=None, params={"param1": Param(type="string")})
        with pytest.raises(ParamValidationError, match="No value passed and Param has no default value"):
            dag.create_dagrun(
                run_id="test_dagrun_missing_param",
                state=State.RUNNING,
                execution_date=TEST_DATE,
            )
        dag = models.DAG("dummy-dag", schedule=None, params={"param1": Param(type="string")})
        with pytest.raises(
            ParamValidationError, match="Invalid input for param param1: None is not of type 'string'"
        ):
            dag.create_dagrun(
                run_id="test_dagrun_missing_param",
                state=State.RUNNING,
                execution_date=TEST_DATE,
                conf={"param1": None},
            )
        dag = models.DAG("dummy-dag", schedule=None, params={"param1": Param(type="string")})
        dag.create_dagrun(
            run_id="test_dagrun_missing_param",
            state=State.RUNNING,
            execution_date=TEST_DATE,
            conf={"param1": "hello"},
        )
    def test_return_date_range_with_num_method(self):