# openai/gym

Switch branches/tags
Nothing to show
75f28fa Aug 24, 2018
5 contributors

### Users who have contributed to this file

152 lines (132 sloc) 5.64 KB
 import sys from six import StringIO from gym import utils from gym.envs.toy_text import discrete import numpy as np MAP = [ "+---------+", "|R: | : :G|", "| : : : : |", "| : : : : |", "| | : | : |", "|Y| : |B: |", "+---------+", ] class TaxiEnv(discrete.DiscreteEnv): """ The Taxi Problem from "Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition" by Tom Dietterich Description: There are four designated locations in the grid world indicated by R(ed), B(lue), G(reen), and Y(ellow). When the episode starts, the taxi starts off at a random square and the passenger is at a random location. The taxi drive to the passenger's location, pick up the passenger, drive to the passenger's destination (another one of the four specified locations), and then drop off the passenger. Once the passenger is dropped off, the episode ends. Observations: There are 500 discrete actions since there are 25 taxi positions, 5 possible locations of the passenger (including the case when the passenger is the taxi), and 4 destination locations. Actions: There are 6 discrete deterministic actions: - 0: move south - 1: move north - 2: move east - 3: move west - 4: pickup passenger - 5: dropoff passenger Rewards: There is a reward of -1 for each action and an additional reward of +20 for delievering the passenger. There is a reward of -10 for executing actions "pickup" and "dropoff" illegally. Rendering: - blue: passenger - magenta: destination - yellow: empty taxi - green: full taxi - other letters: locations """ metadata = {'render.modes': ['human', 'ansi']} def __init__(self): self.desc = np.asarray(MAP,dtype='c') self.locs = locs = [(0,0), (0,4), (4,0), (4,3)] nS = 500 nR = 5 nC = 5 maxR = nR-1 maxC = nC-1 isd = np.zeros(nS) nA = 6 P = {s : {a : [] for a in range(nA)} for s in range(nS)} for row in range(5): for col in range(5): for passidx in range(5): for destidx in range(4): state = self.encode(row, col, passidx, destidx) if passidx < 4 and passidx != destidx: isd[state] += 1 for a in range(nA): # defaults newrow, newcol, newpassidx = row, col, passidx reward = -1 done = False taxiloc = (row, col) if a==0: newrow = min(row+1, maxR) elif a==1: newrow = max(row-1, 0) if a==2 and self.desc[1+row,2*col+2]==b":": newcol = min(col+1, maxC) elif a==3 and self.desc[1+row,2*col]==b":": newcol = max(col-1, 0) elif a==4: # pickup if (passidx < 4 and taxiloc == locs[passidx]): newpassidx = 4 else: reward = -10 elif a==5: # dropoff if (taxiloc == locs[destidx]) and passidx==4: done = True reward = 20 elif (taxiloc in locs) and passidx==4: newpassidx = locs.index(taxiloc) else: reward = -10 newstate = self.encode(newrow, newcol, newpassidx, destidx) P[state][a].append((1.0, newstate, reward, done)) isd /= isd.sum() discrete.DiscreteEnv.__init__(self, nS, nA, P, isd) def encode(self, taxirow, taxicol, passloc, destidx): # (5) 5, 5, 4 i = taxirow i *= 5 i += taxicol i *= 5 i += passloc i *= 4 i += destidx return i def decode(self, i): out = [] out.append(i % 4) i = i // 4 out.append(i % 5) i = i // 5 out.append(i % 5) i = i // 5 out.append(i) assert 0 <= i < 5 return reversed(out) def render(self, mode='human'): outfile = StringIO() if mode == 'ansi' else sys.stdout out = self.desc.copy().tolist() out = [[c.decode('utf-8') for c in line] for line in out] taxirow, taxicol, passidx, destidx = self.decode(self.s) def ul(x): return "_" if x == " " else x if passidx < 4: out[1+taxirow][2*taxicol+1] = utils.colorize(out[1+taxirow][2*taxicol+1], 'yellow', highlight=True) pi, pj = self.locs[passidx] out[1+pi][2*pj+1] = utils.colorize(out[1+pi][2*pj+1], 'blue', bold=True) else: # passenger in taxi out[1+taxirow][2*taxicol+1] = utils.colorize(ul(out[1+taxirow][2*taxicol+1]), 'green', highlight=True) di, dj = self.locs[destidx] out[1+di][2*dj+1] = utils.colorize(out[1+di][2*dj+1], 'magenta') outfile.write("\n".join(["".join(row) for row in out])+"\n") if self.lastaction is not None: outfile.write(" ({})\n".format(["South", "North", "East", "West", "Pickup", "Dropoff"][self.lastaction])) else: outfile.write("\n") # No need to return anything for human if mode != 'human': return outfile