%PDF-1.3 1 0 obj << /Kids [ 4 0 R 5 0 R 6 0 R 7 0 R 8 0 R 9 0 R 10 0 R 11 0 R 12 0 R ] /Type /Pages /Count 9 >> endobj 2 0 obj << /Subject (Neural Information Processing Systems http\072\057\057nips\056cc\057) /Publisher (Curran Associates\054 Inc\056) /Language (en\055US) /Created (2014) /EventType (Poster) /Description-Abstract (Our understanding of the neural computations that underlie the ability of animals to choose among options has advanced through a synthesis of computational modeling\054 brain imaging and behavioral choice experiments\056 Yet\054 there remains a gulf between theories of preference learning and accounts of the real\054 economic choices that humans face in daily life\054 choices that are usually between some amount of money and an item\056 In this paper\054 we develop a theory of magnitude\055sensitive preference learning that permits an agent to rationally infer its preferences for items compared with money options of different magnitudes\056 We show how this theory yields classical and anomalous supply\055demand curves and predicts choices for a large panel of risky lotteries\056 Accurate replications of such phenomena without recourse to utility functions suggest that the theory proposed is both psychologically realistic and econometrically viable\056) /Producer (PyPDF2) /Title (Magnitude\055sensitive preference formation\140) /Date (2014) /ModDate (D\07220151202101709\05508\04700\047) /Published (2014) /Type (Conference Proceedings) /firstpage (1080) /Book (Advances in Neural Information Processing Systems 27) /Description (Paper accepted and presented at the Neural Information Processing Systems Conference \050http\072\057\057nips\056cc\057\051) /Editors (Z\056 Ghahramani and M\056 Welling and C\056 Cortes and N\056D\056 Lawrence and K\056Q\056 Weinberger) /Author (Nisheeth Srivastava\054 Ed Vul\054 Paul R\056 Schrater) /lastpage (1088) >> endobj 3 0 obj << /Type /Catalog /Pages 1 0 R >> endobj 4 0 obj << /Contents 13 0 R /Parent 1 0 R 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