1 | import json
|
---|
2 | import random
|
---|
3 | import logging
|
---|
4 | from random import randint
|
---|
5 | from time import time
|
---|
6 | from typing import cast
|
---|
7 | from utils.plot_trace import plot_trace
|
---|
8 | from utils.runners import run_session
|
---|
9 | from geniusweb.actions.Accept import Accept
|
---|
10 | from geniusweb.actions.Action import Action
|
---|
11 | from geniusweb.actions.Offer import Offer
|
---|
12 | from geniusweb.actions.PartyId import PartyId
|
---|
13 | from geniusweb.bidspace.AllBidsList import AllBidsList
|
---|
14 | from geniusweb.inform.ActionDone import ActionDone
|
---|
15 | from geniusweb.inform.Finished import Finished
|
---|
16 | from geniusweb.inform.Inform import Inform
|
---|
17 | from geniusweb.inform.Settings import Settings
|
---|
18 | from geniusweb.inform.YourTurn import YourTurn
|
---|
19 | from geniusweb.issuevalue.Bid import Bid
|
---|
20 | from geniusweb.issuevalue.Domain import Domain
|
---|
21 | from geniusweb.party.Capabilities import Capabilities
|
---|
22 | from geniusweb.party.DefaultParty import DefaultParty
|
---|
23 | from geniusweb.profile.utilityspace.LinearAdditiveUtilitySpace import (
|
---|
24 | LinearAdditiveUtilitySpace,
|
---|
25 | )
|
---|
26 | from geniusweb.profileconnection.ProfileConnectionFactory import (
|
---|
27 | ProfileConnectionFactory,
|
---|
28 | )
|
---|
29 | from geniusweb.progress.ProgressTime import ProgressTime
|
---|
30 | from geniusweb.references.Parameters import Parameters
|
---|
31 | from tudelft_utilities_logging.ReportToLogger import ReportToLogger
|
---|
32 |
|
---|
33 | from .utils.opponent_model import OpponentModel
|
---|
34 |
|
---|
35 |
|
---|
36 | class Tjaronchery10Agent(DefaultParty):
|
---|
37 | """
|
---|
38 | Template of a Python geniusweb agent.
|
---|
39 | """
|
---|
40 |
|
---|
41 | def __init__(self):
|
---|
42 | super().__init__()
|
---|
43 | self.logger: ReportToLogger = self.getReporter()
|
---|
44 | self.tatic = 1
|
---|
45 | self.domain: Domain = None
|
---|
46 | self.parameters: Parameters = None
|
---|
47 | self.profile: LinearAdditiveUtilitySpace = None
|
---|
48 | self.progress: ProgressTime = None
|
---|
49 | self.me: PartyId = None
|
---|
50 | self.other: str = None
|
---|
51 | self.settings: Settings = None
|
---|
52 | self.storage_dir: str = None
|
---|
53 | self.datii = ""
|
---|
54 | self.last_received_bid: Bid = None
|
---|
55 | self.counter = 0
|
---|
56 | self.minicount = 0
|
---|
57 | self.flag = 0
|
---|
58 | self.dupli = 0.00
|
---|
59 | self.opponent_model: OpponentModel = None
|
---|
60 | self.logger.log(logging.INFO, "party is initialized")
|
---|
61 |
|
---|
62 | def notifyChange(self, data: Inform):
|
---|
63 | """MUST BE IMPLEMENTED
|
---|
64 | This is the entry point of all interaction with your agent after is has been initialised.
|
---|
65 | How to handle the received data is based on its class type.
|
---|
66 |
|
---|
67 | Args:
|
---|
68 | info (Inform): Contains either a request for action or information.
|
---|
69 | """
|
---|
70 |
|
---|
71 | # a Settings message is the first message that will be send to your
|
---|
72 | # agent containing all the information about the negotiation session.
|
---|
73 |
|
---|
74 | if isinstance(data, Settings):
|
---|
75 | self.settings = cast(Settings, data)
|
---|
76 | self.me = self.settings.getID()
|
---|
77 | # progress towards the deadline has to be tracked manually through the use of the Progress object
|
---|
78 | self.progress = self.settings.getProgress()
|
---|
79 |
|
---|
80 | self.parameters = self.settings.getParameters()
|
---|
81 | self.storage_dir = self.parameters.get("storage_dir")
|
---|
82 |
|
---|
83 | # the profile contains the preferences of the agent over the domain
|
---|
84 | profile_connection = ProfileConnectionFactory.create(
|
---|
85 | data.getProfile().getURI(), self.getReporter()
|
---|
86 | )
|
---|
87 | self.profile = profile_connection.getProfile()
|
---|
88 | self.domain = self.profile.getDomain()
|
---|
89 | profile_connection.close()
|
---|
90 |
|
---|
91 | # ActionDone informs you of an action (an offer or an accept)
|
---|
92 | # that is performed by one of the agents (including yourself).
|
---|
93 | elif isinstance(data, ActionDone):
|
---|
94 | action = cast(ActionDone, data).getAction()
|
---|
95 | actor = action.getActor()
|
---|
96 |
|
---|
97 | # ignore action if it is our action
|
---|
98 | if actor != self.me:
|
---|
99 | # obtain the name of the opponent, cutting of the position ID.
|
---|
100 | self.other = str(actor).rsplit("_", 1)[0]
|
---|
101 |
|
---|
102 | if self.counter > 3:
|
---|
103 | with open(f"{self.storage_dir}/{self.other}datatactic.txt", "r") as t:
|
---|
104 | shura = t.readline()
|
---|
105 | if shura.__contains__("tac2"):
|
---|
106 | self.tatic = 2
|
---|
107 | t.close()
|
---|
108 | else:
|
---|
109 | with open(f"{self.storage_dir}/{self.other}data.txt", "r") as f:
|
---|
110 | lines = f.readlines()
|
---|
111 | last_lines = lines[-3:]
|
---|
112 | if last_lines[0] == '0\n' and last_lines[1] == '0\n' and last_lines[2] == '0\n':
|
---|
113 | # print("THIS IS MACABBIIIIIIIIIIIIIIIIIIIIIII")
|
---|
114 | self.tatic = 2
|
---|
115 | with open(f"{self.storage_dir}/{self.other}datatactic.txt", "a") as x:
|
---|
116 | x.write("tac2")
|
---|
117 | x.close()
|
---|
118 | else:
|
---|
119 | self.tatic = 1
|
---|
120 | f.close()
|
---|
121 | self.flag = 1
|
---|
122 | # process action done by opponent
|
---|
123 | self.opponent_action(action)
|
---|
124 | # YourTurn notifies you that it is your turn to act
|
---|
125 | elif isinstance(data, YourTurn):
|
---|
126 | # execute a turn
|
---|
127 | self.my_turn()
|
---|
128 |
|
---|
129 | # Finished will be send if the negotiation has ended (through agreement or deadline)
|
---|
130 | elif isinstance(data, Finished):
|
---|
131 | self.save_data()
|
---|
132 | # terminate the agent MUST BE CALLED
|
---|
133 | self.logger.log(logging.INFO, "party is terminating:")
|
---|
134 | super().terminate()
|
---|
135 | else:
|
---|
136 | self.logger.log(logging.WARNING, "Ignoring unknown info " + str(data))
|
---|
137 |
|
---|
138 | def getCapabilities(self) -> Capabilities:
|
---|
139 | """MUST BE IMPLEMENTED
|
---|
140 | Method to indicate to the protocol what the capabilities of this agent are.
|
---|
141 | Leave it as is for the ANL 2022 competition
|
---|
142 |
|
---|
143 | Returns:
|
---|
144 | Capabilities: Capabilities representation class
|
---|
145 | """
|
---|
146 | return Capabilities(
|
---|
147 | set(["SAOP"]),
|
---|
148 | set(["geniusweb.profile.utilityspace.LinearAdditive"]),
|
---|
149 | )
|
---|
150 |
|
---|
151 | def send_action(self, action: Action):
|
---|
152 | """Sends an action to the opponent(s)
|
---|
153 |
|
---|
154 | Args:
|
---|
155 | action (Action): action of this agent
|
---|
156 | """
|
---|
157 | self.getConnection().send(action)
|
---|
158 |
|
---|
159 | # give a description of your agent
|
---|
160 | def getDescription(self) -> str:
|
---|
161 | """MUST BE IMPLEMENTED
|
---|
162 | Returns a description of your agent. 1 or 2 sentences.
|
---|
163 |
|
---|
164 | Returns:
|
---|
165 | str: Agent description
|
---|
166 | """
|
---|
167 | return "mine agent for the ANL 2022 competition"
|
---|
168 |
|
---|
169 | def opponent_action(self, action):
|
---|
170 | """Process an action that was received from the opponent.
|
---|
171 |
|
---|
172 | Args:
|
---|
173 | action (Action): action of opponent
|
---|
174 | """
|
---|
175 | # if it is an offer, set the last received bid
|
---|
176 | if isinstance(action, Offer):
|
---|
177 | # create opponent model if it was not yet initialised
|
---|
178 | if self.opponent_model is None:
|
---|
179 | self.opponent_model = OpponentModel(self.domain)
|
---|
180 |
|
---|
181 | bid = cast(Offer, action).getBid()
|
---|
182 |
|
---|
183 | # update opponent model with bid
|
---|
184 | self.opponent_model.update(bid)
|
---|
185 | # set bid as last received
|
---|
186 | self.last_received_bid = bid
|
---|
187 |
|
---|
188 | def my_turn(self):
|
---|
189 | """This method is called when it is our turn. It should decide upon an action
|
---|
190 | to perform and send this action to the opponent.
|
---|
191 | """
|
---|
192 | # check if the last received offer is good enough
|
---|
193 | if self.minicount == 0:
|
---|
194 | try:
|
---|
195 | with open(f"{self.storage_dir}/{self.other}counter.txt", "r") as tt:
|
---|
196 | a = 1
|
---|
197 | content = tt.readlines()
|
---|
198 | tt.close()
|
---|
199 | for line in content:
|
---|
200 | for i in line:
|
---|
201 | # Checking for the digit in
|
---|
202 | # the string
|
---|
203 | if i.isdigit() == True:
|
---|
204 | a += int(i)
|
---|
205 | num = a
|
---|
206 | self.counter = num
|
---|
207 | print("this is macabiiiiiiiiiiiiiii")
|
---|
208 | print(num)
|
---|
209 | try:
|
---|
210 | with open(f"{self.storage_dir}/{self.other}counter.txt", "w") as ttt:
|
---|
211 | ttt.write(num.__str__())
|
---|
212 | ttt.close()
|
---|
213 | except FileNotFoundError:
|
---|
214 | print("file does not exist1 :(")
|
---|
215 | except FileNotFoundError:
|
---|
216 | print("file does not exist counter :(")
|
---|
217 | self.minicount = 1
|
---|
218 |
|
---|
219 | if self.accept_condition(self.last_received_bid):
|
---|
220 | # if so, accept the offer
|
---|
221 | self.datii = self.profile.getUtility(self.last_received_bid).__str__()
|
---|
222 | action = Accept(self.me, self.last_received_bid)
|
---|
223 | else:
|
---|
224 | # if not, find a bid to propose as counter offer
|
---|
225 | bid = self.find_bid()
|
---|
226 |
|
---|
227 | action = Offer(self.me, bid)
|
---|
228 | self.datii = self.profile.getUtility(bid).__str__()
|
---|
229 |
|
---|
230 | # send the action
|
---|
231 | self.send_action(action)
|
---|
232 |
|
---|
233 | def save_data(self):
|
---|
234 | """This method is called after the negotiation is finished. It can be used to store data
|
---|
235 | for learning capabilities. Note that no extensive calculations can be done within this method.
|
---|
236 | Taking too much time might result in your agent being killed, so use it for storage only.
|
---|
237 | """
|
---|
238 | data = "Data for learning (see README.md)"
|
---|
239 | progress = self.progress.get(time() * 1000)
|
---|
240 | s = self.datii
|
---|
241 | t = self.me.__str__()
|
---|
242 | r = self.settings.getID().__str__()
|
---|
243 | y = self.other
|
---|
244 | # path = self.storage_dir
|
---|
245 | # path = f"{self.storage_dir}/{y}"
|
---|
246 | # print(path)
|
---|
247 |
|
---|
248 | if progress == 1:
|
---|
249 | s = 0
|
---|
250 | with open(f"{self.storage_dir}/{y}data.txt", "a") as f:
|
---|
251 | f.write(f"{s}\n")
|
---|
252 | f.close()
|
---|
253 | with open(f"{self.storage_dir}/{y}datatactic.txt", "a") as t:
|
---|
254 | t.close()
|
---|
255 | if self.counter == 0:
|
---|
256 | print("OPEN FILEEEEEEEEE")
|
---|
257 | with open(f"{self.storage_dir}/{y}counter.txt", "a") as x:
|
---|
258 | x.write("1\n")
|
---|
259 | x.close()
|
---|
260 |
|
---|
261 |
|
---|
262 | ###########################################################################################
|
---|
263 | ################################## Example methods below ##################################
|
---|
264 | ###########################################################################################
|
---|
265 |
|
---|
266 | def accept_condition(self, bid: Bid) -> bool:
|
---|
267 | if bid is None:
|
---|
268 | return False
|
---|
269 |
|
---|
270 | # progress of the negotiation session between 0 and 1 (1 is deadline)
|
---|
271 | progress = self.progress.get(time() * 1000)
|
---|
272 |
|
---|
273 | # very basic approach that accepts if the offer is valued above 0.7 and
|
---|
274 | # 95% of the time towards the deadline has passed
|
---|
275 | # rand_b = 0.9
|
---|
276 | my_bid = self.find_bid()
|
---|
277 | # num = self.profile.getUtility(my_bid)
|
---|
278 | if self.tatic == 2:
|
---|
279 | conditions = [
|
---|
280 | self.profile.getUtility(bid) > 0.25,
|
---|
281 | progress > 0.8
|
---|
282 | ]
|
---|
283 |
|
---|
284 | else:
|
---|
285 | conditions = [
|
---|
286 | self.profile.getUtility(bid) > 0.9,
|
---|
287 | # progress > 0.8,
|
---|
288 | ]
|
---|
289 | return all(conditions)
|
---|
290 |
|
---|
291 | def find_bid(self) -> Bid:
|
---|
292 | # compose a list of all possible bids
|
---|
293 | domain = self.profile.getDomain()
|
---|
294 | all_bids = AllBidsList(domain)
|
---|
295 |
|
---|
296 | best_bid_score = 0.0
|
---|
297 | best_bid = None
|
---|
298 |
|
---|
299 | # take 500 attempts to find a bid according to a heuristic score
|
---|
300 | if self.tatic == 2:
|
---|
301 | for _ in range(1000):
|
---|
302 | bid = all_bids.get(randint(0, all_bids.size() - 1))
|
---|
303 | bid_score = self.score_bid(bid)
|
---|
304 | #bid_score = self.profile.getUtility(bid)
|
---|
305 |
|
---|
306 | if 0.5 < bid_score < 0.9:
|
---|
307 | best_bid_score, best_bid = bid_score, bid
|
---|
308 |
|
---|
309 | else:
|
---|
310 | for _ in range(1000):
|
---|
311 | bid = all_bids.get(randint(0, all_bids.size() - 1))
|
---|
312 | # bid_score = self.score_bid(bid)
|
---|
313 | bid_score = self.profile.getUtility(bid)
|
---|
314 | if bid_score > best_bid_score:
|
---|
315 | best_bid_score, best_bid = bid_score, bid
|
---|
316 |
|
---|
317 | return best_bid
|
---|
318 |
|
---|
319 | def score_bid(self, bid: Bid, alpha: float = 0.95, eps: float = 0.1) -> float:
|
---|
320 | """Calculate heuristic score for a bid
|
---|
321 |
|
---|
322 | Args:
|
---|
323 | bid (Bid): Bid to score
|
---|
324 | alpha (float, optional): Trade-off factor between self interested and
|
---|
325 | altruistic behaviour. Defaults to 0.95.
|
---|
326 | eps (float, optional): Time pressure factor, balances between conceding
|
---|
327 | and Boulware behaviour over time. Defaults to 0.1.
|
---|
328 |
|
---|
329 | Returns:
|
---|
330 | float: score
|
---|
331 | """
|
---|
332 | progress = self.progress.get(time() * 1000)
|
---|
333 |
|
---|
334 | our_utility = float(self.profile.getUtility(bid))
|
---|
335 |
|
---|
336 | time_pressure = 0.8 - progress ** (1 / eps)
|
---|
337 | score = alpha * time_pressure * our_utility
|
---|
338 | #score = our_utility
|
---|
339 |
|
---|
340 | if self.opponent_model is not None:
|
---|
341 | opponent_utility = self.opponent_model.get_predicted_utility(bid)
|
---|
342 | opponent_score = (1.0 - alpha * time_pressure) * opponent_utility
|
---|
343 | score += opponent_score
|
---|
344 |
|
---|
345 | return score
|
---|