p0, q = map(int, input().split())

# Initialize f with 0.5 for all p
f = [0.5] * 101
threshold = 1e-9

while True:
    new_f = [0.0] * 101
    max_change = 0.0
    for p in range(101):
        p_used = max(0, p - q)
        p_not_used = min(100, p + q)
        
        # Calculate w and d
        w = (1 - p / 100) / 3
        d = (2 + p / 100) / 6
        
        # Probability terms
        prob_method_used = p / 100
        prob_method_not_used = (100 - p) / 100
        
        # Compute the term involving f[p_used] and f[p_not_used]
        term = d * (prob_method_used * f[p_used] + prob_method_not_used * f[p_not_used])
        
        new_f_p = w + term
        new_f[p] = new_f_p
        
        # Update maximum change
        change = abs(new_f_p - f[p])
        if change > max_change:
            max_change = change
    
    # Check for convergence
    if max_change < threshold:
        break
    
    # Update f for next iteration
    f = new_f

# Calculate the total probability
p_total = 1/3 + (1/3) * f[p0]

# Output with sufficient precision
print("{0:.10f}".format(p_total))