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This paper shows how we can combine logical representations of actions and decision theory in such a manner that seems natural for both. In particular we assume an axiomatization of the domain in terms of situation calculus, using what is…

Artificial Intelligence · Computer Science 2013-02-18 David L. Poole

Recent work has considered theoretical models for the behavior of agents with specific behavioral biases: rather than making decisions that optimize a given payoff function, the agent behaves inefficiently because its decisions suffer from…

Computer Science and Game Theory · Computer Science 2017-06-06 Jon Kleinberg , Sigal Oren , Manish Raghavan

We study how linear orders can be employed to realise choice functions for which the set of potential choices is restricted, i.e., the possible choice is not possible among the full powerset of all alternatives. In such restricted settings,…

Artificial Intelligence · Computer Science 2025-09-05 Kai Sauerwald , Kenneth Skiba , Eduardo Fermé , Thomas Meyer

Rationality is frequently associated with making the best possible decisions. It's widely acknowledged that humans, as rational beings, have limitations in their decision-making capabilities. Nevertheless, recent advancements in fields,…

Computers and Society · Computer Science 2023-11-03 Dibakar Das

An agent acquires a costly flexible signal before making a decision. We explore to what degree knowledge of the agent's information costs helps predict her behavior. We establish an impossibility result: learning costs alone generate no…

Theoretical Economics · Economics 2023-04-05 Elliot Lipnowski , Doron Ravid

We study how to infer new choices from prior choices using the framework of choice functions, a unifying mathematical framework for decision-making based on sets of preference orders. In particular, we define the natural (most conservative)…

Artificial Intelligence · Computer Science 2024-12-02 Arne Decadt , Alexander Erreygers , Jasper De Bock

In this paper, we make a review on the concepts of rationality across several different fields, namely in economics, psychology and evolutionary biology and behavioural ecology. We review how processes like natural selection can help us…

Artificial Intelligence · Computer Science 2018-12-03 Catarina Moreira

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

The notion of preferences plays an important role in many disciplines including service robotics which is concerned with scenarios in which robots interact with humans. These interactions can be favored by robots taking human preferences…

We consider the challenge of preference elicitation in systems that help users discover the most desirable item(s) within a given database. Past work on preference elicitation focused on structured models that provide a factored…

Artificial Intelligence · Computer Science 2012-07-19 Ronen I. Brafman , Carmel Domshlak , Tanya Kogan

Rational decision making in its linguistic description means making logical decisions. In essence, a rational agent optimally processes all relevant information to achieve its goal. Rationality has two elements and these are the use of…

Artificial Intelligence · Computer Science 2019-02-14 Tshilidzi Marwala

Social marketing is becoming increasingly important in contemporary business. Central to social marketing is quantifying how consumers choose between alternatives and how they influence each other. This work considers a new but simple…

Social and Information Networks · Computer Science 2014-05-05 Jeremy Chen

If Economics is understood as the study of the interactions among intentional agents, being rationality the main source of intentional behavior, the mathematical tools that it requires must be extended to capture systemic effects. Here we…

Theoretical Economics · Economics 2023-09-13 Fernando Tohmé

Environments built for people are increasingly operated by a new class of economic actors: LLM-powered software agents making decisions on our behalf. These decisions range from our purchases to travel plans to medical treatment selection.…

Artificial Intelligence · Computer Science 2026-02-25 Manuel Cherep , Chengtian Ma , Abigail Xu , Maya Shaked , Pattie Maes , Nikhil Singh

Affordances, a foundational concept in human-computer interaction and design, have traditionally been explained by direct-perception theories, which assume that individuals perceive action possibilities directly from the environment.…

Human-Computer Interaction · Computer Science 2025-01-22 Yi-Chi Liao , Christian Holz

We study an online linear classification problem, in which the data is generated by strategic agents who manipulate their features in an effort to change the classification outcome. In rounds, the learner deploys a classifier, and an…

Machine Learning · Computer Science 2017-10-24 Jinshuo Dong , Aaron Roth , Zachary Schutzman , Bo Waggoner , Zhiwei Steven Wu

Compact representations of objects is a common concept in computer science. Automated planning can be viewed as a case of this concept: a planning instance is a compact implicit representation of a graph and the problem is to find a path (a…

Artificial Intelligence · Computer Science 2014-01-24 Christer Bäckström , Peter Jonsson

We consider multi-agent argumentation, where each agent's view of the arguments is encoded as an argumentation framework (AF). Then we study deliberative processes than can occur on this basis. We think of a deliberative process as taking…

Logic in Computer Science · Computer Science 2014-08-08 Truls Pedersen , Sjur Dyrkolbotn

Given the family $P$ of all nonempty subsets of a set $U$ of alternatives, a choice over $U$ is a function $c \colon \Omega \to P$ such that $\Omega \subseteq P$ and $c(B) \subseteq B$ for all menus $B \in \Omega$. A choice is total if…

Logic in Computer Science · Computer Science 2022-12-05 Domenico Cantone , Alfio Giarlotta , Pietro Maugeri , Stephen Watson

As artificial agents become increasingly capable, what internal structure is *necessary* for an agent to act competently under uncertainty? Classical results show that optimal control can be *implemented* using belief states or world…

Machine Learning · Computer Science 2026-04-03 Aran Nayebi