Majority illusion occurs in a social network when the majority of the network vertices belong to a certain type but the majority of each vertex's neighbours belong to a different type, therefore creating the wrong perception, i.e., the illusion, that the majority type is different from the actual one. From a system engineering point of view, this motivates the search for algorithms to detect and, where possible, correct this undesirable phenomenon. In this paper we initiate the computational study of majority illusion in social networks, providing NP-hardness and parametrised complexity results for its occurrence and elimination.
 

Identifying and Eliminating Majority Illusion in Social Networks

Regret Matching Notebook


In single-elimination knockout tournaments, participants face each other based on a starting seeding and progress to the next rounds by beating their direct opponents.
In this paper we initiate the study of coalitional knockout tournaments, which generalise single-elimination knockout tournaments by allowing groups of players, or coalitions, to strategically select one of their members to take part in the tournament, following the starting seeding. We investigate the algorithmic properties of pure strategies Nash equilibria in these games under various setups, i.e., whether or not choices can be made at each round and whether or not tournament progression is important to the group. Despite the more complex tournament structure when compared to single-elimination, we provide tractable algorithms for all cases. Our results can be applied to those tournaments where pre-play selection plays an important role, such as sport events or elections with run-off.

Equilibrium Computation For Knockout Tournaments Played By Groups


We study political parties that strategically place their candidates in districts so to maximise the number of their nominees that get elected.In each district, voters rank the nominated candidates and elect the plurality winners. After studying equilibrium existence in restricted instances, we show that deciding the existence of pure Nash equilibria for these games is Σ2P-complete, for the hardness part of which we reduce from ∃∃!-3SAT.

Computing Nash Equilibria for District-based Nominations

GTEP: Game Theory and Economic Paradigms / MAS: Multiagent Systems

poster

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines. AAAI-23 is the Thirty-Seventh AAAI Conference on Artificial Intelligence. The theme of this conference is to create collaborative bridges within and beyond AI. Like previous AAAI conferences, AAAI-23 will feature technical paper presentations, special tracks, invited speakers, workshops, tutorials, poster sessions, senior member presentations, competitions, and exhibit programs, and two new activities: a Bridge Program and a Lab Program. Many of these activities are tailored to the theme of bridges and all are selected according to the highest standards, with additional programs for students and young researchers. 
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AAAI 2023

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines.

EAAI: Model AI Assignments I

**Session Chair:** Nisarg Shah

Oral Session 2A1-3

technical paper

AAMAS (International Conference on Autonomous Agents and Multiagent Systems) is the largest and most influential conference in the area of agents and multiagent systems. The aim of the conference is to bring together researchers and practitioners in all areas of agent technology and to provide a single, high-profile, internationally renowned forum for research in the theory and practice of autonomous agents and multiagent systems. AAMAS is the flagship conference of the non-profit International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).

The AAMAS conference series was initiated in 2002 in Bologna, Italy as a joint event comprising the 6th International Conference on Autonomous Agents (AA), the 5th International Conference on Multiagent Systems (ICMAS), and the 9th International Workshop on Agent Theories, Architectures, and Languages (ATAL).

Subsequent AAMAS conferences have been held in Melbourne, Australia (July 2003), New York City, NY, USA (July 2004), Utrecht, The Netherlands (July 2005), Hakodate, Japan (May 2006), Honolulu, Hawaii, USA (May 2007), Estoril, Portugal (May 2008), Budapest, Hungary (May 2009), Toronto, Canada (May 2010), Taipei, Taiwan (May 2011), Valencia, Spain (June 2012), Minnesota, USA (May 2013), Paris, France (May 2014), Istanbul, Turkey (May 2015), Singapore (May 2016), São Paulo (2017) and Stockholm, Sweden (2018), Montreal (May 2019), Auckland (May 2020, Virtual), London (May 2021, Virtual).

A ticket is required to attend this event, please register using the link below:

https://aamas2022-conference.auckland.ac.nz/attending/registration/

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AAMAS 2022

AAMAS (International Conference on Autonomous Agents and Multiagent Systems) is the largest and most influential conference in the area of agents and multiagent systems. The aim of the conference is to bring together researchers and practitioners in all areas of agent technology and to provide a single, high-profile, internationally renowned forum for research in the theory and practice of autonomous agents and multiagent systems. AAMAS is the flagship conference of the non-profit International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).

Paolo Turrini

4

3

SHORT BIO

Presentations

Identifying and Eliminating Majority Illusion in Social Networks

Regret Matching Notebook

Equilibrium Computation For Knockout Tournaments Played By Groups

Computing Nash Equilibria for District-based Nominations

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