Problem 83 can be solved with A* exactly like the we did in problem 81. The only code that needs to be changed is the neighbors function `neigh`

and the estimated cost-to-goal function `est`

. Everything else can be reused from problem 81.

```
(defn euler-83 []
(let [mat (load-matrix "/zzz/work/matrix.txt")
m (count mat)
n (count (first mat))
cost (fn [[i j]] (nth (nth mat (dec i)) (dec j)))
start [1 1]
goal [m n]
goal? (fn [e] (= e goal))
est (fn [[i j]] 0)
neigh (fn [[i j]]
(merge
(when (< i m) {[(inc i) j] (cost [(inc i) j])})
(when (< j n) {[i (inc j)] (cost [i (inc j)])})
(when (< 1 i) {[(dec i) j] (cost [(dec i) j])})
(when (< 1 j) {[i (dec j)] (cost [i (dec j)])})))
path (a*-search est neigh start goal?)]
(reduce + (map cost path))))
(time (euler-83))
```

With `est`

set to always return zero, the A* search becomes effectively a memory-hungry version of Dijkstra’s Algorithm.