To solve the given optimization problem using Gurobi, we need to formulate the objective function and constraints based on the provided information.

The objective function is to minimize $4.1 \times \text{hours worked by Ringo} + 6.3 \times \text{hours worked by Hank} + 7.72 \times \text{hours worked by Laura}$.

Constraints are as follows:
- The computer competence ratings for Ringo, Hank, and Laura are 7, 14, and 10 respectively.
- The total combined computer competence rating from hours worked by Ringo and Laura must be at least 19.
- The total combined computer competence rating from hours worked by Ringo and Hank must be at least 20.
- The total combined computer competence rating from hours worked by all three (Ringo, Hank, and Laura) must be at least 20.
- $6 \times \text{hours worked by Hank} - 4 \times \text{hours worked by Laura} \geq 0$.
- The total combined computer competence rating from hours worked by Ringo and Hank has to be at most 52.

Given that the hours worked by Ringo and Hank can be fractional, but the hours worked by Laura must be a whole number, we will use continuous variables for Ringo and Hank, and an integer variable for Laura.

Here is how you could implement this in Gurobi using Python:

```python
from gurobipy import *

# Create a model
m = Model("Optimization_Problem")

# Define the variables
Ringo_hours = m.addVar(vtype=GRB.CONTINUOUS, name="hours_worked_by_Ringo")
Hank_hours = m.addVar(vtype=GRB.CONTINUOUS, name="hours_worked_by_Hank")
Laura_hours = m.addVar(vtype=GRB.INTEGER, name="hours_worked_by_Laura")

# Define the objective function
m.setObjective(4.1 * Ringo_hours + 6.3 * Hank_hours + 7.72 * Laura_hours, GRB.MINIMIZE)

# Define the constraints
m.addConstr(7 * Ringo_hours + 10 * Laura_hours >= 19, name="Ringo_Laura_min_19")
m.addConstr(7 * Ringo_hours + 14 * Hank_hours >= 20, name="Ringo_Hank_min_20")
m.addConstr(7 * Ringo_hours + 14 * Hank_hours + 10 * Laura_hours >= 20, name="All_min_20")
m.addConstr(6 * Hank_hours - 4 * Laura_hours >= 0, name="Hank_Laura_ratio")
m.addConstr(7 * Ringo_hours + 14 * Hank_hours <= 52, name="Ringo_Hank_max_52")

# Optimize the model
m.optimize()

# Print the results
if m.status == GRB.OPTIMAL:
    print("Optimal solution found:")
    print(f"Hours worked by Ringo: {Ringo_hours.x}")
    print(f"Hours worked by Hank: {Hank_hours.x}")
    print(f"Hours worked by Laura: {Laura_hours.x}")
else:
    print("No optimal solution found")
```