## Problem Description and Symbolic Representation

The problem involves minimizing an objective function subject to several constraints. The variables are 'intrusion analysts' and 'honeypots', denoted as $x_1$ and $x_2$ respectively.

### Symbolic Variables
- $x_1$ : intrusion analysts
- $x_2$ : honeypots

### Objective Function
The objective function to minimize is $6.44x_1 + 9.58x_2$.

### Constraints
1. $5x_1 + 18x_2 \geq 40$ (Power consumption minimum)
2. $4x_1 + 8x_2 \geq 13$ (Computational load minimum)
3. $6x_1 - 4x_2 \geq 0$ (Intrusion analysts vs Honeypots balance)
4. $5x_1 + 18x_2 \leq 86$ (Power consumption maximum)
5. $4x_1 + 8x_2 \leq 59$ (Computational load maximum)
6. $x_1 \geq 0$ and $x_1$ is an integer (Non-negative integer intrusion analysts)
7. $x_2 \geq 0$ and $x_2$ is an integer (Non-negative integer honeypots)

## Gurobi Code

```python
import gurobipy as gp

# Create a new model
m = gp.Model("intrusion_analysts_honeypots")

# Define variables
x1 = m.addVar(name="intrusion_analysts", vtype=gp.GRB.INTEGER)  # Intrusion analysts
x2 = m.addVar(name="honeypots", vtype=gp.GRB.INTEGER)  # Honeypots

# Objective function: Minimize 6.44 * x1 + 9.58 * x2
m.setObjective(6.44 * x1 + 9.58 * x2, gp.GRB.MINIMIZE)

# Constraints
m.addConstr(5 * x1 + 18 * x2 >= 40, name="power_min")  # Power consumption minimum
m.addConstr(4 * x1 + 8 * x2 >= 13, name="computational_load_min")  # Computational load minimum
m.addConstr(6 * x1 - 4 * x2 >= 0, name="balance")  # Intrusion analysts vs Honeypots balance
m.addConstr(5 * x1 + 18 * x2 <= 86, name="power_max")  # Power consumption maximum
m.addConstr(4 * x1 + 8 * x2 <= 59, name="computational_load_max")  # Computational load maximum

# Solve the model
m.optimize()

# Print the solution
if m.status == gp.GRB.OPTIMAL:
    print("Optimal Solution:")
    print(f"Intrusion Analysts: {x1.varValue}")
    print(f"Honeypots: {x2.varValue}")
    print(f"Objective: {m.objVal}")
else:
    print("No optimal solution found")
```

## Symbolic Representation in JSON

```json
{
    "sym_variables": [
        ["x1", "intrusion analysts"],
        ["x2", "honeypots"]
    ],
    "objective_function": "6.44 * x1 + 9.58 * x2",
    "constraints": [
        "5 * x1 + 18 * x2 >= 40",
        "4 * x1 + 8 * x2 >= 13",
        "6 * x1 - 4 * x2 >= 0",
        "5 * x1 + 18 * x2 <= 86",
        "4 * x1 + 8 * x2 <= 59",
        "x1 is an integer and x1 >= 0",
        "x2 is an integer and x2 >= 0"
    ]
}
```