**Apache Airflow version**: 2.0.0a1

**What happened**:

On my dev environment I have a lot of DAG runs with failed tasks, where the *downstream* task instances then have been set to `upstream_failed`. The scheduler is now refusing to schedule more instances for such DAGs.

The scheduler looks for such task instances that are not in the `State.finished` set:

https://github.com/apache/airflow/blob/db3fe0926bb75008311eed804052c90bfa912424/airflow/jobs/scheduler_job.py#L1482-L1488

However, `State.finished` is currently not a proper inverse of *running* states, it only includes success, failed, and skipped:

https://github.com/apache/airflow/blob/db3fe0926bb75008311eed804052c90bfa912424/airflow/utils/state.py#L110-L114

What is missing is the task instance `upstream_failed` state, so currently my log is being filled (very rapidly) with:

```
[2020-10-18 13:22:18,503] {{scheduler_job.py:1658}} INFO - DAG test_dag already has 26 active runs, not queuing any more tasks
```

Those 26 'active runs' are simply dag runs that failed and have 'upstream_failed' task instances.

Either `upstream_failed` should be added to `State.finished`, or the Scheduler task instance test should explicitly take that state into account.
tests/jobs/test_scheduler_job.py
Test if a task instance will be added if the dag is updated
        """
        dag = DAG(dag_id='test_scheduler_add_new_task', start_date=DEFAULT_DATE)
        BashOperator(task_id='dummy', dag=dag, owner='airflow', bash_command='echo test')
        scheduler = SchedulerJob()
        scheduler.dagbag.bag_dag(dag, root_dag=dag)
        scheduler.dagbag.sync_to_db()
        session = settings.Session()
        orm_dag = session.query(DagModel).get(dag.dag_id)
        assert orm_dag is not None
        scheduler = SchedulerJob()
        scheduler.processor_agent = mock.MagicMock()
        dag = scheduler.dagbag.get_dag('test_scheduler_add_new_task', session=session)
        scheduler._create_dag_runs([orm_dag], session)
        drs = DagRun.find(dag_id=dag.dag_id, session=session)
        assert len(drs) == 1
        dr = drs[0]
        tis = dr.get_task_instances()
        self.assertEqual(len(tis), 1)
        BashOperator(task_id='dummy2', dag=dag, owner='airflow', bash_command='echo test')
        SerializedDagModel.write_dag(dag=dag)
        scheduled_tis = scheduler._schedule_dag_run(dr, 0, session)
        session.flush()
        assert scheduled_tis == 2
        drs = DagRun.find(dag_id=dag.dag_id, session=session)
        assert len(drs) == 1
        dr = drs[0]
        tis = dr.get_task_instances()
        self.assertEqual(len(tis), 2)
    def test_runs_respected_after_clear(self):