Adversarial Learned Fair Representations using Dampening and Stacking

Autor: Knobbout, Max

As more decisions in our daily life become automated, the need to have machine learning algorithms that make fair decisions increases. In fair representation learning we are tasked with finding a suitable representation of the data in which a sensiti

Externí odkaz: http://arxiv.org/abs/2203.08637

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Towards a Framework for Predicting Opportunism in Multi-agent Systems

Autor: Luo, Jieting, Meyer, John-Jules, Knobbout, Max, Sub Algemeen Artificial Intelligence, Sub Intelligent Systems, Artificial Intellligence, Intelligent Systems

Publikováno v: Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 1616. International Foundation for Autonomous Agents and Multiagent Systems
STARTPAGE=1616;TITLE=Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems

Opportunism is a behavior that takes advantage of knowledge asymmetry and results in promoting agents' own value and demoting others' value. We propose a framework to reason about agents' opportunistic propensity and characterize the situation where

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=narcis______::cde4e934611859a3e63e68ab9dac62bc
https://dspace.library.uu.nl/handle/1874/359167

Reasoning about Dynamic Normative Systems

Autor: Knobbout, Max, Dastani, Mehdi, Meyer, John-Jules Charles, Fermé, Eduardo, Leite, J., Intelligent Systems, Sub Intelligent Systems

Publikováno v: Logics in Artificial Intelligence-14th European Conference (JELIA), 8761. Springer

The use of normative systems is widely accepted as an effective approach to control and regulate the behaviour of agents in multiagent systems. When norms are added to a normative system, the behaviour of such a system changes. As of yet, there is no

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=narcis______::b51679f8fd7c9d89ab7524a03366cc31
https://dspace.library.uu.nl/handle/1874/306048

A Formal Account of Opportunism in Multi-agent Systems

Autor: Luo, J., Sub Algemeen Artificial Intelligence, Intelligent Systems

Opportunistic behavior is a selfish behavior that takes advantage of knowledge asymmetry and results in promoting agents' own value but demoting other agents' value. It is commonly existing in business transactions and social interactions, thereby ga

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=narcis______::0a114d533a1055e08ac8bc6baa51465c
https://dspace.library.uu.nl/handle/1874/363344