adventofcode2022/day16/search.py

98 lines
3.1 KiB
Python

G = []
for line in open("input"):
words = line.split()
valve = words[1]
rate = int(''.join(x for x in words[4] if x.isdigit()))
edges = [x.strip(", ") for x in words[9:]]
G.append((valve, rate, edges))
#print(G)
import sys, os; sys.path.append(os.path.join(os.path.dirname(__file__), "../lib"))
import astar
def search():
V = sorted(v for v,_,_ in G) # vertices
B = {v: 1<<i for i, v in enumerate(V)} # bitmasks
E = {B[v]: [B[e] for e in edges] for v,_,edges in G} # edge[b] -> b
R = {B[v]: r for v,r,_ in G} # rewards: R[b] = reward
all_closed = sum(B.values())
all_open = 0
minutes = 30
start = (B['AA'], minutes, all_closed)
# A* search minimizes costs
# it can't maxmize anything
# so we'll borrow an idea from https://github.com/morgoth1145/advent-of-code/blob/2bf7c157e37b3e0a65deedc6c88e42297d813d1d/2022/16/solution.py
# and instead say that the cost of moving from one node to the next
# is equal to the potential pressure we could have released from the closed pipes
# or, in other words, we'll keep track of how much pressure builds up in
# closed pipes instead of how much pressure is released from open pipes
# let's shink the graph by finding the shortest path between
# every pair of rooms (floyd-warshall), and then building a graph which only has
# paths from the starting room to rooms with a valve
# and from any room with a valve to any other room with a valve
# our heuristic cost has to be <= the actual cost of getting to the goal
# here's a simple one:
# we know it takes at least 1 minute to open a valve,
# and at least another minute to walk to the valve
# so we can assign at least cost 2*pressure(closed_valves) to this node
# (unless there is only 1 minute left)
def heuristic(node):
v, minutes, closed = node
if closed == all_open:
m = minutes
else:
m = min(minutes,1)
return m*pressure(closed)
def pressure(bits):
pressure = 0
for v,r in R.items():
if bits&v:
pressure += r
return pressure
def is_goal(n):
v, minutes, closed = n
return minutes == 0
info = {}
def neighbors(n):
v, minutes, closed = n
if minutes not in info:
print(info)
info[minutes] = 0
info[minutes] += 1
if minutes <= 0:
pass
elif closed == all_open:
c = pressure(closed) * minutes
yield c, (v, 0, closed)
else:
c = pressure(closed)
if v&closed and R[v]:
yield c, (v, minutes-1, closed & ~v)
for e in E[v]:
yield c, (e, minutes-1, closed)
c, _, path = astar.search(start, is_goal, neighbors, heuristic)
print(c)
print(pressure(all_closed)*30 - c)
#maxpair = []
#def pairs():
# O = sorted(best.keys())
# for i in range(len(O)):
# for j in range(i,len(O)):
# if not O[i] & O[j]:
# yield(best[O[i]]+best[O[j]])
#print(max(pairs()))
search()