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We consider a model where an agent has a repeated decision to make and wishes to maximize their total payoff. Payoffs are influenced by an action taken by the agent, but also an unknown state of the world that evolves over time. Before…

Computer Science and Game Theory · Computer Science 2021-01-20 Nicole Immorlica , Ian Kash , Brendan Lucier

Most decision theories, including expected utility theory, rank dependent utility theory and cumulative prospect theory, assume that investors are only interested in the distribution of returns and not in the states of the economy in which…

Portfolio Management · Quantitative Finance 2014-07-03 Carole Bernard , Franck Moraux , Ludger Rueschendorf , Steven Vanduffel

Designing recommendation systems that serve content aligned with time varying preferences requires proper accounting of the feedback effects of recommendations on human behavior and psychological condition. We argue that modeling the…

Information Retrieval · Computer Science 2022-08-09 Mihaela Curmei , Andreas Haupt , Dylan Hadfield-Menell , Benjamin Recht

We define a novel neuro-symbolic framework, argumentative reward learning, which combines preference-based argumentation with existing approaches to reinforcement learning from human feedback. Our method improves prior work by generalising…

Artificial Intelligence · Computer Science 2022-10-05 Francis Rhys Ward , Francesco Belardinelli , Francesca Toni

In feature-based dynamic pricing, a seller sets appropriate prices for a sequence of products (described by feature vectors) on the fly by learning from the binary outcomes of previous sales sessions ("Sold" if valuation $\geq$ price, and…

Machine Learning · Computer Science 2022-04-04 Jianyu Xu , Yu-Xiang Wang

Aggregated data in real world recommender applications often feature fat-tailed distributions of the number of times individual items have been rated or favored. We propose a model to simulate such data. The model is mainly based on social…

Physics and Society · Physics 2012-08-14 Marcel Blattner , Matus Medo

Predicting future consumer behaviour is one of the most challenging problems for large scale retail firms. Accurate prediction of consumer purchase pattern enables better inventory planning and efficient personalized marketing strategies.…

Machine Learning · Computer Science 2020-10-15 Ankur Verma

We consider a model where an agent is must choose between alternatives that each provide only an imprecise description of the world (e.g. linguistic expressions). The set of alternatives is closed under logical conjunction and disjunction,…

Theoretical Economics · Economics 2024-09-11 Evan Piermont , Marcus Pivato

A widely applied diversification paradigm is the naive diversification choice heuristic. It stipulates that an economic agent allocates equal decision weights to given choice alternatives independent of their individual characteristics.…

Economics · Quantitative Finance 2016-11-10 Enrico G. De Giorgi , Ola Mahmoud

Learning user preferences for products based on their past purchases or reviews is at the cornerstone of modern recommendation engines. One complication in this learning task is that some users are more likely to purchase products or review…

Information Retrieval · Computer Science 2023-03-08 Wanning Chen , Mohsen Bayati

In many settings -- like market research and social choice -- people may be presented with unfamiliar options. Classical mechanisms may perform poorly because they fail to incentivize people to learn about these options, or worse, encourage…

Theoretical Economics · Economics 2025-07-22 Modibo K. Camara , Nicole Immorlica , Brendan Lucier

This chapter presents a review of the dividend discount models starting from the basic models (Williams 1938, Gordon and Shapiro 1956) to more recent and complex models (Ghezzi and Piccardi 2003, Barbu et al. 2017, D'Amico and De Blasis…

General Finance · Quantitative Finance 2020-01-03 Guglielmo D'Amico , Riccardo De Blasis

In consumer theory, ranking available objects by means of preference relations yields the most common description of individual choices. However, preference-based models assume that individuals: (1) give their preferences only between pairs…

Machine Learning · Computer Science 2023-02-02 Alessio Benavoli , Dario Azzimonti , Dario Piga

Organisms and ecological groups accumulate evidence to make decisions. Classic experiments and theoretical studies have explored this process when the correct choice is fixed during each trial. However, we live in a constantly changing…

Neurons and Cognition · Quantitative Biology 2015-10-01 Alan Veliz-Cuba , Zachary P. Kilpatrick , Kresimir Josic

This paper develops a new model of business cycles. The model is economical in that it is solved with an aggregate demand-aggregate supply diagram, and the effects of shocks and policies are obtained by comparative statics. The model builds…

Theoretical Economics · Economics 2022-03-22 Pascal Michaillat , Emmanuel Saez

This chapter provides a tutorial that the reader can follow towards analyzing discounting data. Previous chapters have already described the breadth of outcomes associated with discounting (Odum et al. 2020) and other background information…

Applications · Statistics 2024-08-08 Christopher T. Franck

Timing decisions are common: when to file your taxes, finish a referee report, or complete a task at work. We ask whether time preferences can be inferred when \textsl{only} task completion is observed. To answer this question, we analyze…

Theoretical Economics · Economics 2019-05-13 Paul Heidhues , Philipp Strack

The well-known theorem of Dybvig, Ingersoll and Ross shows that the long zero-coupon rate can never fall. This result, which, although undoubtedly correct, has been regarded by many as surprising, stems from the implicit assumption that the…

General Finance · Quantitative Finance 2015-09-29 Dorje C. Brody , Lane P. Hughston

The rapid growth of e-commerce has made people accustomed to shopping online. Before making purchases on e-commerce websites, most consumers tend to rely on rating scores and review information to make purchase decisions. With this…

Information Retrieval · Computer Science 2020-07-07 Yingqiang Ge , Shuyuan Xu , Shuchang Liu , Zuohui Fu , Fei Sun , Yongfeng Zhang

We consider the problem of decision-making with side information and unbounded loss functions. Inspired by probably approximately correct learning model, we use a slightly different model that incorporates the notion of side information in…

Machine Learning · Computer Science 2007-07-13 Majid Fozunbal , Ton Kalker
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