--- /dev/null
+#!/usr/bin/python -u
+
+#NOTE: The -u option is required for unbuffered stdin/stdout.
+# If stdin/stdout are buffered, the manager program will not recieve any messages and assume that the agent has timed out.
+
+'''
+ vixen.py - A sample Stratego AI for the UCC Programming Competition 2012
+
+ Written in python, the slithery language
+
+ author Sam Moore (matches) [SZM]
+ website http://matches.ucc.asn.au/stratego
+ git git.ucc.asn.au/progcomp2012.git
+'''
+
+from basic_python import *
+from path import *
+
+
+
+class Vixen(BasicAI):
+ " Python based AI, improves upon Asmodeus by taking into account probabilities, and common paths "
+ def __init__(self):
+ #sys.stderr.write("Vixen initialised...\n")
+ BasicAI.__init__(self)
+
+
+ #self.bombScores = {'1' : -0.9 , '2' : -0.8 , '3' : -0.5 , '4' : 0.1, '5' : 0.1, '6' : 0.3, '7' : 0.7, '8' : 1 , '9' : 0.6, 's' : 0}
+ #self.bombScores = {'1' : -0.9 , '2' : -0.8 , '3' : -0.5 , '4' : -0.5, '5' : -0.4, '6' : -0.5, '7' : -0.2, '8' : 1.0 , '9' : -0.1, 's' : -0.2}
+ self.suicideScores = {'1' : -0.5 , '2' : -0.4 , '3' : -0.35, '4' : -0.25, '5' : -0.2, '6' : 0.0, '7' : 0.1, '8' : -1.0 , '9' : 0.0, 's' : -0.4}
+ self.killScores = {'1' : 1.0 , '2' : 0.9 , '3' : 0.9 , '4' : 0.8, '5' : 0.8, '6' : 0.8, '7' : 0.8, '8' : 0.9 , '9' : 0.7, 's' : 1.0}
+ self.riskScores = {'1' : 0.0, '2' : 0.1, '3' : 0.2, '4': 0.4, '5': 0.6, '6': 0.7, '7':0.8, '8': 0.0, '9' : 1.0, 's' : 0.1}
+
+
+
+
+
+ def MakeMove(self):
+ #sys.stderr.write("Vixen MakingMove...\n")
+ " Over-rides the default BasicAI.MakeMove function "
+
+ moveList = []
+ for unit in self.units:
+ if unit.mobile() == False:
+ continue
+
+ scores = {"LEFT":0, "RIGHT":0, "UP":0, "DOWN":0}
+
+
+ for target in self.enemyUnits:
+ if target == unit:
+ continue
+ path = PathFinder().pathFind((unit.x, unit.y), (target.x, target.y), self.board)
+ if path == False or len(path) == 0:
+ continue
+ #moveList.append({"unit":unit, "direction":path[0], "score":self.CalculateScore(unit, target, path)})
+ scores[path[0]] += self.CalculateScore(unit, target, path)
+
+ bestScore = sorted(scores.items(), key = lambda e : e[1], reverse=True)[0]
+ moveList.append({"unit":unit, "direction":bestScore[0], "score":bestScore[1]})
+
+
+ if len(moveList) == 0:
+ print "NO_MOVE"
+ return True
+
+ moveList.sort(key = lambda e : e["score"], reverse=True)
+ #sys.stderr.write("vixen - best move: " + str(moveList[0]["unit"].x) + " " + str(moveList[0]["unit"].y) + " " + moveList[0]["direction"] + " [ score = " + str(moveList[0]["score"]) + " ]\n")
+ if moveList[0]["score"] == 0:
+ print "NO_MOVE"
+ return True
+
+
+ print str(moveList[0]["unit"].x) + " " + str(moveList[0]["unit"].y) + " " + moveList[0]["direction"]
+ return True
+
+
+ def tailFactor(self, pathLength):
+ #if pathLength >= len(self.tailFactors) or pathLength <= 0:
+ # return 0.0
+ #return self.tailFactors[pathLength]
+ #return 0.5 * (1.0 + pow(pathLength, 0.75))
+ return 1.0 / pathLength
+
+
+ def CalculateScore(self, attacker, defender, path):
+ p = move(attacker.x, attacker.y, path[0], 1)
+
+
+ total = 0.0
+ count = 0.0
+ for rank in ranks:
+ prob = self.rankProbability(defender, rank)
+ if prob > 0.0:
+ #sys.stderr.write(" " + str(attacker.rank) + " vs. " + str(rank) + " [" + str(prob) + "] score " + str(self.combatScore(attacker.rank, rank, len(path))) + "\n")
+ total += prob * self.combatScore(attacker.rank, rank, len(path))
+ count += 1
+
+
+ #if count > 1:
+ # total = total / count + self.riskScore(attacker.rank)
+
+
+ total = total * self.tailFactor(len(path))
+ #HACK - Prevent "oscillating" by decreasing the value of backtracks
+ if len(path) > 1 and len(attacker.positions) > 1 and attacker.positions[1][0] == p[0] and attacker.positions[1][1] == p[1]:
+ total = total / 100
+ #sys.stderr.write("Total score for " + str(attacker) + " vs. " + str(defender) + " is " + str(total) + "\n")
+ return total
+
+ def combatScore(self, attackerRank, defenderRank, pathLength):
+ if defenderRank == 'F':
+ return 1.0
+ elif defenderRank == 'B':
+ return self.bombScore(attackerRank)
+ elif defenderRank == 's' and attackerRank == '1' and pathLength == 2:
+ return self.suicideScore(attackerRank)
+ elif defenderRank == '1' and attackerRank == 's' and pathLength != 2:
+ return self.killScore(attackerRank)
+
+ if valuedRank(attackerRank) > valuedRank(defenderRank):
+ return self.killScore(defenderRank)
+ elif valuedRank(attackerRank) < valuedRank(defenderRank):
+ return self.suicideScore(attackerRank)
+ return self.killScore(defenderRank) + self.suicideScore(attackerRank)
+
+ def killScore(self, defenderRank):
+ return self.killScores[defenderRank]
+
+ def bombScore(self, attackerRank):
+ if attackerRank == '8':
+ return 1.0
+ else:
+ return 0.0
+
+ def suicideScore(self, attackerRank):
+ return self.suicideScores[attackerRank]
+
+ def riskScore(self, attackerRank):
+ return self.riskScores[attackerRank]
+
+ def rankProbability(self, target, targetRank):
+ if targetRank == '+' or targetRank == '?':
+ return 0.0
+ if target.rank == targetRank:
+ return 1.0
+ elif target.rank != '?':
+ return 0.0
+
+ total = 0.0
+ for rank in ranks:
+ if rank == '+' or rank == '?':
+ continue
+ elif rank == 'F' or rank == 'B':
+ if target.lastMoved < 0:
+ total += self.hiddenEnemies[rank]
+ else:
+ total += self.hiddenEnemies[rank]
+
+ if total == 0.0:
+ return 0.0
+ return float(float(self.hiddenEnemies[targetRank]) / float(total))
+
+
+
+
+
+
+
+if __name__ == "__main__":
+ vixen = Vixen()
+ if vixen.Setup():
+ while vixen.MoveCycle():
+ pass
+
git.ucc.asn.au / progcomp2012.git / blobdiff
UCC git Repository :: git.ucc.asn.au