source: src/main/java/agents/BayesianAgent.java@ 346

Last change on this file since 346 was 127, checked in by Wouter Pasman, 6 years ago

#41 ROLL BACK of rev.126 . So this version is equal to rev. 125

File size: 21.3 KB
RevLine 
[127]1package agents;
2
3import java.util.ArrayList;
4import java.util.Random;
5
6import agents.bayesianopponentmodel.BayesianOpponentModelScalable;
7import agents.bayesianopponentmodel.OpponentModel;
8import agents.bayesianopponentmodel.OpponentModelUtilSpace;
9import genius.core.Agent;
10import genius.core.Bid;
11import genius.core.BidIterator;
12import genius.core.SupportedNegotiationSetting;
13import genius.core.actions.Accept;
14import genius.core.actions.Action;
15import genius.core.actions.EndNegotiation;
16import genius.core.actions.Offer;
17import genius.core.analysis.BidPoint;
18import genius.core.analysis.BidSpace;
19import genius.core.issue.Issue;
20import genius.core.utility.AdditiveUtilitySpace;
21import genius.core.xml.SimpleElement;
22
23/**
24 * Wrapper for opponentmodelspace, so that it is a neat utilityspace that we can
25 * give to the bidspace.
26 *
27 * @author Tim Baarslag & Dmytro Tykhonov
28 */
29
30public class BayesianAgent extends Agent {
31
32 private Action messageOpponent;
33 private Bid myLastBid = null;
34 protected Action myLastAction = null;
35 protected Bid fOpponentPreviousBid = null;
36
37 private enum ACTIONTYPE {
38 START, OFFER, ACCEPT, BREAKOFF
39 };
40
41 /** See paper. Standard = TIT_FOR_TAT */
42 private enum STRATEGY {
43 SMART, SERIAL, RESPONSIVE, RANDOM, TIT_FOR_TAT
44 };
45
46 private STRATEGY fStrategy = STRATEGY.TIT_FOR_TAT;
47 private int fSmartSteps;
48 protected OpponentModel fOpponentModel;
49 private static final double CONCESSIONFACTOR = 0.04;
50 private static final double ALLOWED_UTILITY_DEVIATION = 0.01;
51 private static final int NUMBER_OF_SMART_STEPS = 0;
52 private ArrayList<Bid> myPreviousBids;
53 private boolean fSkipDistanceCalc = false;
54 private boolean logging = !false;
55
56 // Class constructor
57 public BayesianAgent() {
58 super();
59 }
60
61 @Override
62 public String getVersion() {
63 return "2.1";
64 }
65
66 @Override
67 public String getName() {
68 return "Bayesian Agent";
69 }
70
71 @Override
72 public void init() {
73 @SuppressWarnings("unused")
74 // cast to ensure AdditiveUtilitySpace
75 AdditiveUtilitySpace a = (AdditiveUtilitySpace) utilitySpace;
76 messageOpponent = null;
77 myLastAction = null;
78 fSmartSteps = 0;
79 myPreviousBids = new ArrayList<Bid>();
80 prepareOpponentModel();
81 }
82
83 protected void prepareOpponentModel() {
84 fOpponentModel = new BayesianOpponentModelScalable(
85 (AdditiveUtilitySpace) utilitySpace);
86 }
87
88 // Class methods
89 @Override
90 public void ReceiveMessage(Action opponentAction) {
91 messageOpponent = opponentAction;
92 }
93
94 private Action proposeInitialBid() throws Exception {
95 Bid lBid = null;
96 // Return (one of the) possible bid(s) with maximal utility.
97 lBid = ((AdditiveUtilitySpace) utilitySpace).getMaxUtilityBid();
98 fSmartSteps = NUMBER_OF_SMART_STEPS;
99 myLastBid = lBid;
100 return new Offer(getAgentID(), lBid);
101 }
102
103 /**
104 *
105 * @param pOppntBid
106 * @return a counterbid that has max util for us and an opponent utility
107 * that is equal to 1-estimated utility of opponent's last bid. Or,
108 * if that bid was done already before, another bid that has same
109 * utility in our space as that counterbid.
110 * @throws Exception
111 */
112 private Bid getNextBid(Bid pOppntBid) throws Exception {
113 if (pOppntBid == null)
114 throw new NullPointerException("pOpptBid=null");
115 if (myLastBid == null)
116 throw new Exception("myLastBid==null");
117 log("Get next bid ...");
118
119 BidSpace bs = new BidSpace(utilitySpace,
120 new OpponentModelUtilSpace(fOpponentModel), false, true);
121 // System.out.println("Bidspace:\n"+bs);
122
123 // compute opponent's concession
124 double opponentConcession = 0.;
125 if (fOpponentPreviousBid == null)
126 opponentConcession = 0;
127 else {
128 double opponentUtil = fOpponentModel
129 .getNormalizedUtility(pOppntBid);
130 double opponentFirstBidUtil = fOpponentModel.getNormalizedUtility(
131 fOpponentModel.fBiddingHistory.get(0));
132 opponentConcession = opponentUtil - opponentFirstBidUtil;
133 }
134 log("opponent Concession:" + opponentConcession);
135
136 // determine our bid point
137 double OurFirstBidOppUtil = fOpponentModel
138 .getNormalizedUtility(myPreviousBids.get(0));
139 double OurTargetBidOppUtil = OurFirstBidOppUtil - opponentConcession;
140 if (OurTargetBidOppUtil > 1)
141 OurTargetBidOppUtil = 1.;
142 if (OurTargetBidOppUtil < OurFirstBidOppUtil)
143 OurTargetBidOppUtil = OurFirstBidOppUtil;
144 log("our target opponent utility=" + OurTargetBidOppUtil);
145
146 // find the target on the pareto curve
147 double targetUtil = bs.ourUtilityOnPareto(OurTargetBidOppUtil);
148 // exclude only the last bid
149 // ArrayList<Bid> excludeBids = new ArrayList<Bid>();
150 // excludeBids.add(myPreviousBids.get(myPreviousBids.size()-1));
151 BidPoint bp = bs.getNearestBidPoint(targetUtil, OurTargetBidOppUtil, .5,
152 .1, myPreviousBids);
153 log("found bid " + bp);
154 return bp.getBid();
155 }
156
157 /**
158 * get a new bid (not done before) that has ourUtility for us.
159 *
160 * @param ourUtility
161 * @return the bid with max opponent utility that is close to ourUtility. or
162 * null if there is no such bid.
163 */
164 Bid getNewBidWithUtil(double ourUtility, BidSpace bs) {
165 BidPoint bestbid = null;
166 double bestbidutil = 0;
167 for (BidPoint p : bs.bidPoints) {
168 if (Math.abs(
169 ourUtility - p.getUtilityA()) < ALLOWED_UTILITY_DEVIATION
170 && p.getUtilityB() > bestbidutil
171 && !myPreviousBids.contains(p.getBid())) {
172 bestbid = p;
173 bestbidutil = p.getUtilityB();
174 }
175 }
176 if (bestbid == null)
177 return null;
178 return bestbid.getBid();
179 }
180
181 private Bid getNextBidSmart(Bid pOppntBid) throws Exception {
182 double lMyUtility, lOppntUtility, lTargetUtility;
183 // Both parties have made an initial bid. Compute associated utilities
184 // from my point of view.
185 lMyUtility = utilitySpace.getUtility(myLastBid);
186 lOppntUtility = utilitySpace.getUtility(pOppntBid);
187 if (fSmartSteps >= NUMBER_OF_SMART_STEPS) {
188 lTargetUtility = getTargetUtility(lMyUtility, lOppntUtility);
189 fSmartSteps = 0;
190 } else {
191 lTargetUtility = lMyUtility;
192 fSmartSteps++;
193 }
194 return getTradeOff(lTargetUtility, pOppntBid);
195 }
196
197 private Bid getTradeOff(double pUtility, Bid pOppntBid) throws Exception {
198 Bid lBid = null;
199 double lExpectedUtility = -100;
200 BidIterator lIter = new BidIterator(utilitySpace.getDomain());
201 // int i=1;
202 while (lIter.hasNext()) {
203 Bid tmpBid = lIter.next();
204 // System.out.println(tmpBid);
205 // System.out.println(String.valueOf(i++));
206 if (Math.abs(utilitySpace.getUtility(tmpBid)
207 - pUtility) < ALLOWED_UTILITY_DEVIATION) {
208 // double lTmpSim = fSimilarity.getSimilarity(tmpBid,
209 // pOppntBid);
210 double lTmpExpecteUtility = fOpponentModel
211 .getNormalizedUtility(tmpBid);
212 if (lTmpExpecteUtility > lExpectedUtility) {
213 lExpectedUtility = lTmpExpecteUtility;
214 lBid = tmpBid;
215 }
216 }
217 } // while
218 return lBid;
219 }
220
221 private Bid proposeNextBid(Bid pOppntBid) throws Exception {
222 Bid lBid = null;
223 switch (fStrategy) {
224 case TIT_FOR_TAT:
225 lBid = getNextBid(pOppntBid);
226 break;
227 case SMART:
228 lBid = getNextBidSmart(pOppntBid);
229 break;
230 default:
231 throw new Exception("unknown strategy " + fStrategy);
232 }
233 myLastBid = lBid;
234 return lBid;
235 }
236
237 @Override
238 public Action chooseAction() {
239 Action lAction = null;
240 ACTIONTYPE lActionType;
241 Bid lOppntBid = null;
242
243 try {
244 lActionType = getActionType(messageOpponent);
245 switch (lActionType) {
246 case OFFER: // Offer received from opponent
247 lOppntBid = ((Offer) messageOpponent).getBid();
248 // if (fOpponentModel.haveSeenBefore(lOppntBid)) {
249 // lAction=myLastAction; break; }
250 // double lDistance = calculateEuclideanDistanceUtilitySpace();
251 // if(myLastAction==null) dumpDistancesToLog(0);
252 System.out.print("Updating beliefs ...");
253 if (myPreviousBids.size() < 8)
254 fOpponentModel.updateBeliefs(lOppntBid);
255 // dumpDistancesToLog(fRound++);
256 System.out.println("Done!");
257 if (myLastAction == null)
258 // Other agent started, lets propose my initial bid.
259 lAction = proposeInitialBid();
260 else {
261 double offeredutil = utilitySpace.getUtility(lOppntBid);
262 // double time=((new
263 // Date()).getTime()-startTime.getTime())/(1000.*totalTime);
264 // double P=Paccept(offeredutil,time);
265 // log("time="+time+" offeredutil="+offeredutil+" accept
266 // probability P="+P);
267 /* if (.05*P>Math.random()) was here too */
268 if (isAcceptableBefore(offeredutil)) {
269 // Opponent bids equally, or outbids my previous bid, so
270 // lets accept
271 lAction = new Accept(getAgentID(), lOppntBid);
272 log("opponent's bid higher than util of my last bid! accepted");
273 } else {
274 Bid lnextBid = proposeNextBid(lOppntBid);
275 lAction = new Offer(getAgentID(), lnextBid);
276
277 // Liviu: it doesn't allow proposing null bid
278 if (lnextBid == null)
279 lnextBid = myPreviousBids
280 .get(myPreviousBids.size() - 1);
281
282 // Propose counteroffer. Get next bid.
283 // Check if utility of the new bid is lower than utility
284 // of the opponent's last bid
285 // if yes then accept last bid of the opponent.
286 // Before 22-12-2010 it was: if (offeredutil*1.03 >=
287 // utilitySpace.getUtility(lnextBid))
288 if (isAcceptableAfter(offeredutil, lnextBid)) {
289 // Opponent bids equally, or outbids my previous
290 // bid, so lets accept
291 lAction = new Accept(getAgentID(), lOppntBid);
292 log("opponent's bid higher than util of my next bid! accepted");
293 }
294
295 }
296 // remember current bid of the opponent as its previous bid
297 fOpponentPreviousBid = lOppntBid;
298 }
299 break;
300 case ACCEPT:
301 case BREAKOFF:
302 // nothing left to do. Negotiation ended, which should be
303 // checked by
304 // Negotiator...
305 break;
306 default:
307 // I am starting, but not sure whether Negotiator checks this,
308 // so
309 // lets check also myLastAction...
310 if (myLastAction == null) {
311 // dumpDistancesToLog(fRound++);
312 lAction = proposeInitialBid();
313 } else
314 // simply repeat last action
315 lAction = myLastAction;
316 break;
317 }
318 } catch (Exception e) {
319 log("Exception in chooseAction:" + e.getMessage());
320 e.printStackTrace();
321 lAction = new Offer(getAgentID(), myLastBid);
322 }
323 myLastAction = lAction;
324 if (myLastAction instanceof Offer) {
325 myPreviousBids.add(((Offer) myLastAction).getBid());
326 myLastBid = ((Offer) myLastAction).getBid();
327 }
328 return lAction;
329 }
330
331 /**
332 * Returns whether the offered utility is acceptable after computing a
333 * counter offer.
334 */
335 protected boolean isAcceptableAfter(double offeredutil, Bid lnextBid)
336 throws Exception {
337 return offeredutil >= utilitySpace.getUtility(lnextBid);
338 }
339
340 /**
341 * Returns whether the offered utility is acceptable before computing a
342 * counter offer.
343 */
344 protected boolean isAcceptableBefore(double offeredutil) throws Exception {
345 return offeredutil * 1.03 >= utilitySpace.getUtility(myLastBid);
346 }
347
348 private ACTIONTYPE getActionType(Action lAction) {
349 ACTIONTYPE lActionType = ACTIONTYPE.START;
350 if (lAction instanceof Offer)
351 lActionType = ACTIONTYPE.OFFER;
352 else if (lAction instanceof Accept)
353 lActionType = ACTIONTYPE.ACCEPT;
354 else if (lAction instanceof EndNegotiation)
355 lActionType = ACTIONTYPE.BREAKOFF;
356 return lActionType;
357 }
358
359 private double getTargetUtility(double myUtility, double oppntUtility) {
360 return myUtility - getConcessionFactor();
361 }
362
363 private double getConcessionFactor() {
364 // The more the agent is willing to concess on its aspiration value, the
365 // higher this factor.
366 return CONCESSIONFACTOR;
367 }
368
369 /**
370 * Prints out debug information only if the fDebug = true
371 *
372 * @param pMessage
373 * - debug informaton to print
374 */
375 private void log(String pMessage) {
376 if (logging)
377 System.out.println(pMessage);
378 }
379
380 private double sq(double x) {
381 return x * x;
382 }
383
384 private double calculateEuclideanDistanceUtilitySpace(double[] pLearnedUtil,
385 double[] pOpponentUtil) {
386 double lDistance = 0;
387 try {
388 for (int i = 0; i < pLearnedUtil.length; i++)
389 lDistance = lDistance + sq(pOpponentUtil[i] - pLearnedUtil[i]);
390 } catch (Exception e) {
391 e.printStackTrace();
392 }
393 lDistance = lDistance
394 / utilitySpace.getDomain().getNumberOfPossibleBids();
395 return lDistance;
396 }
397
398 private double calculateEuclideanDistanceWeghts(double[] pExpectedWeight) {
399 double lDistance = 0;
400 int i = 0;
401 try {
402 for (Issue lIssue : utilitySpace.getDomain().getIssues()) {
403 lDistance = lDistance + sq(
404 fNegotiation.getOpponentWeight(this, lIssue.getNumber())
405 - pExpectedWeight[i]);
406 i++;
407 }
408 } catch (Exception e) {
409 e.printStackTrace();
410 }
411 return lDistance / i;
412 }
413
414 private double calculatePearsonDistanceUtilitySpace(
415 double[] pLearnedUtility, double[] pOpponentUtil) {
416 double lDistance = 0;
417 double lAverageLearnedUtil = 0;
418 double lAverageOriginalUtil = 0;
419 // calculate average values
420 for (int i = 0; i < pLearnedUtility.length; i++) {
421 lAverageLearnedUtil = lAverageLearnedUtil + pLearnedUtility[i];
422 lAverageOriginalUtil = lAverageOriginalUtil + pOpponentUtil[i];
423 }
424 lAverageLearnedUtil = lAverageLearnedUtil
425 / (utilitySpace.getDomain().getNumberOfPossibleBids());
426 lAverageOriginalUtil = lAverageOriginalUtil
427 / (utilitySpace.getDomain().getNumberOfPossibleBids());
428 // calculate the distance itself
429 double lSumX = 0;
430 double lSumY = 0;
431 for (int i = 0; i < pLearnedUtility.length; i++) {
432 lDistance = lDistance + (pLearnedUtility[i] - lAverageLearnedUtil)
433 * (pOpponentUtil[i] - lAverageOriginalUtil);
434 lSumX = lSumX + sq(pLearnedUtility[i] - lAverageLearnedUtil);
435 lSumY = lSumY + sq(pOpponentUtil[i] - lAverageOriginalUtil);
436
437 }
438
439 return lDistance / (Math.sqrt(lSumX * lSumY));
440 }
441
442 private double calculatePearsonDistanceWeghts(double[] pExpectedWeight) {
443 double lDistance = 0;
444 double lAverageLearnedWeight = 0;
445 double lAverageOriginalWeight = 0;
446 int i = 0;
447 try {
448 for (Issue lIssue : utilitySpace.getDomain().getIssues()) {
449 lAverageLearnedWeight = lAverageLearnedWeight
450 + pExpectedWeight[i];
451 lAverageOriginalWeight = lAverageOriginalWeight + fNegotiation
452 .getOpponentWeight(this, lIssue.getNumber());
453 i++;
454 }
455 } catch (Exception e) {
456 e.printStackTrace();
457 }
458 lAverageLearnedWeight = lAverageLearnedWeight / (i);
459 lAverageOriginalWeight = lAverageOriginalWeight / (i);
460
461 // calculate the distance itself
462 i = 0;
463 double lSumX = 0;
464 double lSumY = 0;
465 try {
466 for (Issue lIssue : utilitySpace.getDomain().getIssues()) {
467 lDistance = lDistance + (fNegotiation.getOpponentWeight(this,
468 lIssue.getNumber()) - lAverageOriginalWeight)
469 * (pExpectedWeight[i] - lAverageLearnedWeight);
470 lSumX = lSumX + sq(
471 fNegotiation.getOpponentWeight(this, lIssue.getNumber())
472 - lAverageOriginalWeight);
473 lSumY = lSumY + sq(pExpectedWeight[i] - lAverageLearnedWeight);
474 i++;
475 }
476 } catch (Exception e) {
477 e.printStackTrace();
478 }
479
480 return lDistance / (Math.sqrt(lSumX * lSumY));
481 }
482
483 private double calculateRankingDistanceUtilitySpaceMonteCarlo(
484 double[] pLearnedUtil, double[] pOpponentUtil) {
485 double lDistance = 0;
486 int lNumberOfPossibleBids = (int) (utilitySpace.getDomain()
487 .getNumberOfPossibleBids());
488 int lNumberOfComparisons = 10000;
489 for (int k = 0; k < lNumberOfComparisons; k++) {
490 int i = (new Random()).nextInt(lNumberOfPossibleBids - 1);
491 int j = (new Random()).nextInt(lNumberOfPossibleBids - 1);
492 if (((pLearnedUtil[i] > pLearnedUtil[j])
493 && (pOpponentUtil[i] > pOpponentUtil[j]))
494 || ((pLearnedUtil[i] < pLearnedUtil[j])
495 && (pOpponentUtil[i] < pOpponentUtil[j]))
496 || ((pLearnedUtil[i] == pLearnedUtil[j])
497 && (pOpponentUtil[i] == pOpponentUtil[j]))) {
498
499 } else
500 lDistance++;
501
502 }
503 return (lDistance) / (lNumberOfComparisons);
504 }
505
506 private double calculateRankingDistanceUtilitySpace(double[] pLearnedUtil,
507 double[] pOpponentUtil) {
508
509 double lDistance = 0;
510 int lNumberOfPossibleBids = (int) (utilitySpace.getDomain()
511 .getNumberOfPossibleBids());
512
513 try {
514 for (int i = 0; i < lNumberOfPossibleBids - 1; i++) {
515 for (int j = i + 1; j < lNumberOfPossibleBids; j++) {
516 // if(i==j) continue;
517 if (Math.signum(pLearnedUtil[i] - pLearnedUtil[j]) != Math
518 .signum(pOpponentUtil[i] - pOpponentUtil[j]))
519 lDistance++;
520
521 } // for
522 } // for
523 } catch (Exception e) {
524 e.printStackTrace();
525 }
526
527 lDistance = 2 * lDistance
528 / (utilitySpace.getDomain().getNumberOfPossibleBids()
529 * (utilitySpace.getDomain().getNumberOfPossibleBids()));
530 return lDistance;
531 }
532
533 private double calculateRankingDistanceWeghts(double pExpectedWeights[]) {
534 double lDistance = 0;
535 double[] lOriginalWeights = new double[utilitySpace.getDomain()
536 .getIssues().size()];
537 int k = 0;
538 try {
539 for (Issue lIssue : utilitySpace.getDomain().getIssues()) {
540 lOriginalWeights[k] = fNegotiation.getOpponentWeight(this,
541 lIssue.getNumber());
542 k++;
543 }
544 } catch (Exception e) {
545 e.printStackTrace();
546 }
547 k = 0;
548 int nrOfIssues = utilitySpace.getDomain().getIssues().size();
549 for (int i = 0; i < nrOfIssues - 1; i++) {
550 for (int j = i + 1; j < nrOfIssues; j++) {
551 k++;
552 double tmpWeightLearned = pExpectedWeights[i];
553 double tmpWeightOriginal = lOriginalWeights[i];
554 double tmpWeight2Learned = pExpectedWeights[j];
555 double tmpWeight2Original = lOriginalWeights[j];
556 if (((tmpWeightLearned > tmpWeight2Learned)
557 && (tmpWeightOriginal > tmpWeight2Original))
558 || ((tmpWeightLearned < tmpWeight2Learned)
559 && (tmpWeightOriginal < tmpWeight2Original))
560 || ((tmpWeightLearned == tmpWeight2Learned)
561 && (tmpWeightOriginal == tmpWeight2Original))) {
562
563 } else
564 lDistance++;
565
566 }
567 }
568 return (lDistance) / (k);
569 }
570
571 protected void dumpDistancesToLog(int pRound) {
572 if (fSkipDistanceCalc)
573 return;
574 System.out.print(getName()
575 + ": calculating distance between the learned space and the original one ...");
576
577 double lExpectedWeights[] = new double[utilitySpace.getDomain()
578 .getIssues().size()];
579 int i = 0;
580 for (Issue lIssue : utilitySpace.getDomain().getIssues()) {
581 lExpectedWeights[i] = fOpponentModel.getExpectedWeight(i);
582 i++;
583 }
584
585 double pLearnedUtil[] = new double[(int) (utilitySpace.getDomain()
586 .getNumberOfPossibleBids())];
587 // HashMap<Bid, Double> pLearnedSpace = new HashMap<Bid, Double>();
588 BidIterator lIter = new BidIterator(utilitySpace.getDomain());
589 i = 0;
590 while (lIter.hasNext()) {
591 Bid lBid = lIter.next();
592 try {
593 pLearnedUtil[i] = fOpponentModel.getNormalizedUtility(lBid);
594 // pLearnedSpace.put(lBid, new Double(pLearnedUtil[i]));
595
596 } catch (Exception e) {
597 e.printStackTrace();
598 }
599 i++;
600 }
601 double pOpponentUtil[] = new double[(int) (utilitySpace.getDomain()
602 .getNumberOfPossibleBids())];
603 // HashMap<Bid, Double> pOpponentSpace = new HashMap<Bid, Double>();
604 lIter = new BidIterator(utilitySpace.getDomain());
605 i = 0;
606 while (lIter.hasNext()) {
607 Bid lBid = lIter.next();
608 try {
609 pOpponentUtil[i] = fNegotiation.getOpponentUtility(this, lBid);
610 // pOpponentSpace.put(lBid, new Double(pOpponentUtil[i]));
611 } catch (Exception e) {
612 e.printStackTrace();
613 }
614 i++;
615 }
616
617 double lEuclideanDistUtil = calculateEuclideanDistanceUtilitySpace(
618 pLearnedUtil, pOpponentUtil);
619 double lEuclideanDistWeights = calculateEuclideanDistanceWeghts(
620 lExpectedWeights);
621 double lRankingDistUtil = 0;
622 if ((int) (utilitySpace.getDomain().getNumberOfPossibleBids()) > 100000)
623 lRankingDistUtil = calculateRankingDistanceUtilitySpaceMonteCarlo(
624 pLearnedUtil, pOpponentUtil);
625 else
626 lRankingDistUtil = calculateRankingDistanceUtilitySpace(
627 pLearnedUtil, pOpponentUtil);
628 double lRankingDistWeights = calculateRankingDistanceWeghts(
629 lExpectedWeights);
630 double lPearsonDistUtil = calculatePearsonDistanceUtilitySpace(
631 pLearnedUtil, pOpponentUtil);
632 double lPearsonDistWeights = calculatePearsonDistanceWeghts(
633 lExpectedWeights);
634 SimpleElement lLearningPerformance = new SimpleElement(
635 "learning_performance");
636 lLearningPerformance.setAttribute("round", String.valueOf(pRound));
637 lLearningPerformance.setAttribute("agent", getName());
638 lLearningPerformance.setAttribute("euclidean_distance_utility_space",
639 String.valueOf(lEuclideanDistUtil));
640 lLearningPerformance.setAttribute("euclidean_distance_weights",
641 String.valueOf(lEuclideanDistWeights));
642 lLearningPerformance.setAttribute("ranking_distance_utility_space",
643 String.valueOf(lRankingDistUtil));
644 lLearningPerformance.setAttribute("ranking_distance_weights",
645 String.valueOf(lRankingDistWeights));
646 lLearningPerformance.setAttribute("pearson_distance_utility_space",
647 String.valueOf(lPearsonDistUtil));
648 lLearningPerformance.setAttribute("pearson_distance_weights",
649 String.valueOf(lPearsonDistWeights));
650 System.out.println("Done!");
651 System.out.println(lLearningPerformance.toString());
652 fNegotiation.addAdditionalLog(lLearningPerformance);
653
654 }
655
656 @Override
657 public SupportedNegotiationSetting getSupportedNegotiationSetting() {
658 return SupportedNegotiationSetting.getLinearUtilitySpaceInstance();
659 }
660
661 @Override
662 public String getDescription() {
663 return "bayesian opponent model to guide offers";
664 }
665}
Note: See TracBrowser for help on using the repository browser.