To address the given optimization problem, we first need to break down the components of the problem into a symbolic representation. This involves identifying the variables, the objective function, and the constraints.

The variables in this problem are:
- `x1`: The number of reconnaissance troops.
- `x2`: The number of military intelligence companies.

The objective function is to maximize: `1.57*x1 + 9.68*x2`.

The constraints are as follows:
1. `12*x1 + 2*x2 >= 48` (Total deployment weight must be at least 48 metric tons).
2. `-8*x1 + 9*x2 >= 0`.
3. `12*x1 + 2*x2 <= 138` (Combined deployment weight must not exceed 138 metric tons).
4. `x1` must be an integer (non-fractional amount of reconnaissance troops).
5. `x2` must be an integer (integer number of military intelligence companies).

Given these components, the symbolic representation of the problem is:

```json
{
  'sym_variables': [('x1', 'reconnaissance troops'), ('x2', 'military intelligence companies')],
  'objective_function': '1.57*x1 + 9.68*x2',
  'constraints': [
    '12*x1 + 2*x2 >= 48',
    '-8*x1 + 9*x2 >= 0',
    '12*x1 + 2*x2 <= 138',
    'x1 is an integer',
    'x2 is an integer'
  ]
}
```

To solve this problem using Gurobi, we can use the following Python code:

```python
from gurobipy import *

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

# Define variables
x1 = m.addVar(vtype=GRB.INTEGER, name="reconnaissance_troops")
x2 = m.addVar(vtype=GRB.INTEGER, name="military_intelligence_companies")

# Set the objective function
m.setObjective(1.57*x1 + 9.68*x2, GRB.MAXIMIZE)

# Add constraints
m.addConstr(12*x1 + 2*x2 >= 48, "total_weight_min")
m.addConstr(-8*x1 + 9*x2 >= 0, "weight_ratio")
m.addConstr(12*x1 + 2*x2 <= 138, "total_weight_max")

# Optimize the model
m.optimize()

# Print the results
if m.status == GRB.OPTIMAL:
    print("Optimal solution found:")
    print(f"Reconnaissance troops: {x1.x}")
    print(f"Military intelligence companies: {x2.x}")
    print(f"Objective function value: {m.objVal}")
else:
    print("No optimal solution found")
```