code: package ch.uzh.ifi.ce.cabne.domains.LLG;
  
  import java.util.Iterator;
  import java.util.List;
  
  import ch.uzh.ifi.ce.cabne.algorithm.BNESolverContext;
  import ch.uzh.ifi.ce.cabne.domains.BidSampler;
  import ch.uzh.ifi.ce.cabne.strategy.Strategy;
  
  public class AusubelBaranovLLGSampler extends BidSampler<Double, Double> {
  	final double alpha, gamma;
  	
  	public AusubelBaranovLLGSampler(double alpha, double gamma, BNESolverContext<Double, Double> context) {
  		super(context);
  		this.alpha = alpha;
  		this.gamma = gamma;
  	}
  
  	public Iterator<Sample> conditionalBidIterator(int i, Double v, Double b, List<Strategy<Double, Double>> s) {		
  		// NOTE: this assumes that global bidder plays truthful, which is only the case with a core-selecting rule.
  		// It's not enough to add a separate code path for i == 2 to make it work for a strategic global bidder.
  		if (i == 2) {
  			throw new RuntimeException("This sampler assumes that the global player is truthful.");
  		}
  		
  		Iterator<double[]> rngiter = context.getRng(2).nextVectorIterator();
  		Iterator<double[]> rngitercorr = context.getRng(1).nextVectorIterator();
  		
  
  		Strategy<Double, Double> slocal = s.get((i + 1) % 2);
  		
  		Iterator<Sample> it = new Iterator<Sample>() {
  			double ncorr = 0.0;
  			double nuncorr = 0.0;
  			@Override
  			public boolean hasNext() {
  				return true;
  			}
  
  			@Override
  			public Sample next() {
  				double[] r;
  				Double result[] = new Double[3];
  				double bopponent, density;
  				
  				if (ncorr < nuncorr * (gamma / (1-gamma))) {
              		// next sample is correlated
              		ncorr++;
              		// 2 * r[0] is the global player's value
              		r = rngitercorr.next();
              		bopponent = slocal.getBid(v);
              		density = 1.0;            		
              	} else {
              		// next sample is uncorrelated
              		nuncorr++;
              		// r[1] is the other local player's value, 2 * r[0] is the global player's value
              		r = rngiter.next();
              		bopponent = slocal.getBid(r[1]); 
              		density = alphaDensity(r[1]);
              	}
              	
      			// bids of local players
  				result[i] = b;
  				result[(i + 1) % 2] = bopponent; 
  				
  				// bid of global player, ignoring the area where the global player wins, and adjusting the density
  				// accordingly (importance sampling)
  				double globalbound = Math.min(b + bopponent, 2.0);
  				density *= 0.5 * globalbound/2.0;
  				
  				result[2] = globalbound * r[0];
  				return new Sample(density, result);
  			}
  		};
  		return it;
  	}
  	
  	public double alphaDensity(double bid) {
  		if (alpha == 1.0) {
  			return 1.0;
  		} else if (alpha == 2.0) {
  			return 2.0 * bid;
  		}
  		return alpha * Math.pow(bid, alpha - 1.0);
  	}
  }
  