## Step 1: Define the symbolic representation of the problem
The problem involves two variables: 'signal platoons' and 'artillery batteries', which we can denote as $x_1$ and $x_2$ respectively. The objective function to maximize is $9x_1 + 5x_2$. The constraints are:
- $13.07x_1 + 18.87x_2 \geq 18$ (minimum deployment weight, but it seems there was a misunderstanding in the problem statement as it directly mentions a minimum deployment weight for each type, not a combined minimum, so we'll consider individual weights and other constraints)
- $18.2x_1 + 6.47x_2 \geq 112$ (total combined logistical capacity)
- $6x_1 - 4x_2 \geq 0$ (relationship between signal platoons and artillery batteries)
- $13.07x_1 + 18.87x_2 \leq 31$ (total deployment weight)
- $18.2x_1 + 6.47x_2 \leq 192$ (total combined logistical capacity upper limit)
- $x_1, x_2$ are integers (non-fractional amounts)

## 2: Correct and Clarify Constraints
Given the problem statement, there seems to be a confusion regarding the minimum deployment weight constraint. We'll focus on the constraints that can be directly derived:
- Individual deployment weights: $13.07x_1$ and $18.87x_2$
- Individual logistical capacities: $18.2x_1$ and $6.47x_2$
The actual constraints to consider are:
1. $13.07x_1 \geq 13.07$ and $18.87x_2 \geq 18.87$ are implied by $x_1 \geq 1$ and $x_2 \geq 1$ if we consider minimum units, but we directly use given constraints.

## 3: Formulate the Symbolic Representation
The symbolic representation is:
- Variables: $x_1$ for 'signal platoons', $x_2$ for 'artillery batteries'
- Objective Function: $9x_1 + 5x_2$
- Constraints:
1. $18.2x_1 + 6.47x_2 \geq 112$
2. $6x_1 - 4x_2 \geq 0$
3. $13.07x_1 + 18.87x_2 \leq 31$
4. $18.2x_1 + 6.47x_2 \leq 192$
5. $x_1, x_2 \geq 0$ and are integers

## 4: Convert to Gurobi Code
```python
import gurobi

# Create a new model
model = gurobi.Model()

# Define variables
x1 = model.addVar(vtype=gurobi.GRB.INTEGER, name="signal_platoons")
x2 = model.addVar(vtype=gurobi.GRB.INTEGER, name="artillery_batteries")

# Objective function
model.setObjective(9 * x1 + 5 * x2, gurobi.GRB.MAXIMIZE)

# Constraints
model.addConstr(18.2 * x1 + 6.47 * x2 >= 112, name="logistical_capacity")
model.addConstr(6 * x1 - 4 * x2 >= 0, name="relationship")
model.addConstr(13.07 * x1 + 18.87 * x2 <= 31, name="deployment_weight")
model.addConstr(18.2 * x1 + 6.47 * x2 <= 192, name="logistical_capacity_upper")

# Optimize
model.optimize()

# Print solution
if model.status == gurobi.GRB.OPTIMAL:
    print("Objective: ", model.objVal)
    print("Signal Platoons: ", x1.varValue)
    print("Artillery Batteries: ", x2.varValue)
else:
    print("No solution found")
```

## 5: Provide Symbolic Representation in Requested Format
```json
{
    'sym_variables': [('x1', 'signal platoons'), ('x2', 'artillery batteries')],
    'objective_function': '9*x1 + 5*x2',
    'constraints': [
        '18.2*x1 + 6.47*x2 >= 112',
        '6*x1 - 4*x2 >= 0',
        '13.07*x1 + 18.87*x2 <= 31',
        '18.2*x1 + 6.47*x2 <= 192',
        'x1, x2 are integers'
    ]
}
```