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Related papers: Information Design of Dynamic Mechanisms

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We study the asymptotic behavior of deterministic, continuous-time imitation dynamics for population games over networks. The basic assumption of this learning mechanism -- encompassing the replicator dynamics -- is that players belonging…

Systems and Control · Electrical Eng. & Systems 2020-10-23 Giacomo Como , Fabio Fagnani , Lorenzo Zino

The theory of distributed conceptual structures, as outlined in this paper, is concerned with the distribution and conception of knowledge. It rests upon two related theories, Information Flow and Formal Concept Analysis, which it seeks to…

Logic in Computer Science · Computer Science 2018-10-12 Robert E. Kent

The dynamics of affective decision making is considered for an intelligent network composed of agents with different types of memory: long-term and short-term memory. The consideration is based on probabilistic affective decision theory,…

Artificial Intelligence · Computer Science 2023-09-04 V. I. Yukalov , E. P. Yukalova

Given a dynamic ordinal game, we deem a strategy sequentially rational if there exist a Bernoulli utility function and a conditional probability system with respect to which the strategy is a maximizer. We establish a complete class theorem…

Theoretical Economics · Economics 2023-12-07 Pierfrancesco Guarino

We present a novel interactive learning protocol that enables training request-fulfilling agents by verbally describing their activities. Unlike imitation learning (IL), our protocol allows the teaching agent to provide feedback in a…

Computation and Language · Computer Science 2021-06-16 Khanh Nguyen , Dipendra Misra , Robert Schapire , Miro Dudík , Patrick Shafto

The interactive game theoretical approach to tactics and behavioral self-organization is developed. Though it uses the interactive game theoretical formalization of dialogues as psycholinguistic phenomena, the crucial role is played by the…

General Mathematics · Mathematics 2007-05-23 Denis V. Juriev

Pursuit-evasion games are ubiquitous in nature and in an artificial world. In nature, pursuer(s) and evader(s) are intelligent agents that can learn from experience, and dynamics (i.e., Newtonian or Lagrangian) is vital for the pursuer and…

Systems and Control · Electrical Eng. & Systems 2021-04-06 Hao Xiong , Huanhui Cao , Lin Zhang , Wenjie Lu

Reinforcement learning (RL) is inspired by the way human infants and animals learn from the environment. The setting is somewhat idealized because, in actual tasks, other agents in the environment have their own goals and behave adaptively…

Computer Science and Game Theory · Computer Science 2023-10-31 Yue Lin , Wenhao Li , Hongyuan Zha , Baoxiang Wang

We study the problem of Bayesian learning in a dynamical system involving strategic agents with asymmetric information. In a series of seminal papers in the literature, this problem has been investigated under a simplifying model where…

Computer Science and Game Theory · Computer Science 2020-07-09 Deepanshu Vasal , Achilleas Anastasopoulos

The distribution of efficient individuals in the economy and the efforts that they will put in if they are hired, there are two important concerns for a technologically advanced firm. wants to open a new branch. The firm does not have…

Computer Science and Game Theory · Computer Science 2025-01-27 Sujata Goala , Mridu Prabal Goswami , Surajit Borkotokey

We present a functional framework for automated mechanism design based on a two-stage game model of strategic interaction between the designer and the mechanism participants, and apply it to several classes of two-player infinite games of…

Computer Science and Game Theory · Computer Science 2012-06-26 Yevgeniy Vorobeychik , Daniel Reeves , Michael P. Wellman

We consider the information design problem in spatial resource competition settings. Agents gather at a location deciding whether to move to another location for possibly higher level of resources, and the utility each agent gets by moving…

Computer Science and Game Theory · Computer Science 2019-09-30 Pu Yang , Krishnamurthy Iyer , Peter Frazier

Pairwise interactions between individuals are taken as fundamental drivers of collective behavior responsible for group cohesion and decision-making. While an individual directly influences only a few neighbors, over time indirect…

Adaptation and Self-Organizing Systems · Physics 2022-04-12 Sulimon Sattari , Udoy S. Basak , Ryan G. James , James P. Crutchfield , Tamiki Komatsuzaki

Information flow type systems enforce the security property of noninterference by detecting unauthorized data flows at compile-time. However, they require precise type annotations, making them difficult to use in practice as much of the…

Programming Languages · Computer Science 2021-02-10 Abhishek Bichhawat , McKenna McCall , Limin Jia

What are the value and form of optimal persuasion when information can be generated only slowly? We study this question in a dynamic model in which a 'sender' provides public information over time subject to a graduality constraint, and a…

Theoretical Economics · Economics 2023-04-19 Matteo Escudé , Ludvig Sinander

Designing protocols enhancing cooperation for multi-agent systems remains a grand challenge. Cheap talk, defined as costless, non-binding communication before formal action, serves as a pivotal solution. However, existing theoretical…

Multiagent Systems · Computer Science 2026-03-03 Zhao Song , Chen Shen , Zhen Wang , The Anh Han

By dynamic planning, we refer to the ability of the human brain to infer and impose motor trajectories related to cognitive decisions. A recent paradigm, active inference, brings fundamental insights into the adaptation of biological…

Artificial Intelligence · Computer Science 2024-11-13 Matteo Priorelli , Ivilin Peev Stoianov

Nature can be seen as informational structure with computational dynamics (info-computationalism), where an (info-computational) agent is needed for the potential information of the world to actualize. Starting from the definition of…

Artificial Intelligence · Computer Science 2013-11-05 Gordana Dodig-Crnkovic

The neural mechanism of memory has a very close relation with the problem of representation in artificial intelligence. In this paper a computational model was proposed to simulate the network of neurons in brain and how they process…

Neurons and Cognition · Quantitative Biology 2020-12-02 Hui Wei

In dynamic settings each economic agent's choices can be revealing of her private information. This elicitation via the rationalization of observable behavior depends each agent's perception of which payoff-relevant contingencies other…

Theoretical Economics · Economics 2021-05-17 Evan Piermont , Peio Zuazo-Garin