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Related papers: Deludedly Agreeing to Agree

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We study how disagreement influences team performance in a dynamic game with positive production externalities. Players can hold different views about the productivity of the available production technologies. This disagreement results in…

General Economics · Economics 2024-07-30 Giampaolo Bonomi

A celebrated 1976 theorem of Aumann asserts that honest, rational Bayesian agents with common priors will never "agree to disagree": if their opinions about any topic are common knowledge, then those opinions must be equal. Economists have…

Computational Complexity · Computer Science 2007-05-23 Scott Aaronson

Despite of being quite similar agreement problems, consensus and general k-set agreement require surprisingly different techniques for proving the impossibility in asynchronous systems with crash failures: Rather than relatively simple…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-03-19 Martin Biely , Peter Robinson , Ulrich Schmid

Information asymmetry in games enables players with the information advantage to manipulate others' beliefs by strategically revealing information to other players. This work considers a double-sided information asymmetry in a Bayesian…

Computer Science and Game Theory · Computer Science 2023-08-29 Tao Li , Quanyan Zhu

Is the world quantum? An active research line in quantum foundations is devoted to exploring what constraints can rule out the postquantum theories that are consistent with experimentally observed results. We explore this question in the…

Text-based misinformation permeates online discourses, yet evidence of people's ability to discern truth from such deceptive textual content is scarce. We analyze a novel TV game show data where conversations in a high-stake environment…

Computation and Language · Computer Science 2024-04-09 Sanchaita Hazra , Bodhisattwa Prasad Majumder

A key challenge in the study of multiagent cooperation is the need for individual agents not only to cooperate effectively, but to decide with whom to cooperate. This is particularly critical in situations when other agents have hidden,…

We study opinion dynamics in a population of interacting adaptive agents voting on a set of complex multidimensional issues. We consider agents which can classify issues into for or against. The agents arrive at the opinions about each…

Physics and Society · Physics 2009-03-11 Renato Vicente , Andre C. R. Martins , Nestor Caticha

A new agent-based, bounded-confidence model for discrete one-dimensional opinion dynamics is presented. The agents interact if their opinions do not differ more than a tolerance parameter. In pairwise interactions, one of the pair, randomly…

Adaptation and Self-Organizing Systems · Physics 2013-02-19 M. Kaan Öztürk

We provide a formal framework accounting for a widespread idea in the theory of economic design: analytically established incompatibilities between given axioms should be qualified by the likelihood of their violation. We define the degree…

Theoretical Economics · Economics 2025-02-20 Pierre Bardier

Artificial Intelligence (AI) systems are increasingly used in high-stakes domains of our life, increasing the need to explain these decisions and to make sure that they are aligned with how we want the decision to be made. The field of…

Artificial Intelligence · Computer Science 2023-06-28 Sofie Goethals , David Martens , Theodoros Evgeniou

Contrary to common belief, common belief is not KD4. If individual belief is KD45, common belief does indeed lose the 5 property and keep the D and 4 properties -- and it has none of the other commonly considered properties of knowledge and…

Artificial Intelligence · Computer Science 2026-02-18 Thomas Ågotnes

We consider an infinite collection of agents who make decisions, sequentially, about an unknown underlying binary state of the world. Each agent, prior to making a decision, receives an independent private signal whose distribution depends…

Computer Science and Game Theory · Computer Science 2012-09-07 Kimon Drakopoulos , Asuman Ozdaglar , John Tsitsiklis

There are many ways we can not know. Even in systems that we created ourselves, as, for example, systems in mathematical logic, Go\"edel and Tarski's theorems impose limits on what we can know. As we try to speak of the real world, things…

History and Philosophy of Physics · Physics 2020-06-04 André C. R. Martins

We provide a novel semantics for belief using simplicial complexes. In our framework, belief satisfies the \textsf{KD45} axioms and rules as well as the ``knowledge implies belief'' axiom ($K\phi \lthen B\phi$); in addition, we adopt the…

Logic in Computer Science · Computer Science 2025-12-17 Philip Sink , Adam Bjorndahl

The collective of autonomous cars is expected to generate almost optimal traffic. In this position paper we discuss the multi-agent models and the verification results of the collective behaviour of autonomous cars. We argue that…

Multiagent Systems · Computer Science 2017-09-11 László Z. Varga

Reliable deployment of machine learning models such as neural networks continues to be challenging due to several limitations. Some of the main shortcomings are the lack of interpretability and the lack of robustness against adversarial…

Machine Learning · Computer Science 2025-02-18 Jon Vadillo , Roberto Santana , Jose A. Lozano

A new theorem on conditions for convergence to consensus of a multiagent time-dependent time-discrete dynamical system is presented. The theorem is build up on the notion of averaging maps. We compare this theorem to results by Moreau (IEEE…

Optimization and Control · Mathematics 2011-01-18 Jan Lorenz , Dirk A. Lorenz

Multi-agent scenarios, like Wigner's friend and Frauchiger-Renner scenarios, can show contradictory results when a non-classical formalism must deal with the knowledge between agents. Such paradoxes are described with multi-modal logic as…

Quantum Physics · Physics 2024-04-19 Sidiney B. Montanhano

When does society eventually learn the truth, or take the correct action, via observational learning? In a general model of sequential learning over social networks, we identify a simple condition for learning dubbed excludability.…

Theoretical Economics · Economics 2024-04-05 Navin Kartik , SangMok Lee , Tianhao Liu , Daniel Rappoport