United Kingdom

AAMAS is the largest and most influential conference in the area of agents and multiagent systems, bringing together researchers and practitioners in all areas of agent technology and providing and internationally renowned high-profile forum for publishing and finding out about the latest developments in the field. AAMAS is the flagship conference of the non-profit International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).  

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AAMAS 2021

Mechanism design has traditionally assumed that the set of participants are fixed and known to the mechanism (the market owner) in advance. However, in practice, the market owner can only directly reach a small number of participants (her neighbours). Hence the owner often needs costly promotions to recruit more participants in order to get desirable outcomes such as social welfare or revenue maximization. In this paper, we propose to incentivize existing participants to invite their neighbours to attract more participants. However, they would not invite each other if they are competitors. We discuss how to utilize the conflict of interest between the participants to incentivize them to invite each other to form larger markets. We will highlight the early solutions and open the floor for discussing the fundamental open questions in the settings of auctions, coalitional games, matching and voting.

Mechanism Design Powered by Social Interactions (Blue Sky Ideas Track)

technical paper

TORS: A Train Unit Shunting and Servicing Simulator

Approximating Spatial Evolutionary Games using Bayesian Networks

Cohorting to Isolate Asymptomatic Spreaders: An Agent-Based Simulation Study on the Mumbai Suburban Railway

Summarising a Framework for the Certification of Reliable Autonomous Systems (JAAMAS Track)

STRATA: Unified Framework for Task Assignments in Large Teams of Heterogeneous Agents (JAAMAS Track)

Multi-Agent Coordination in Adversarial Environments through Signal Mediated Strategies

Strategyproof Facility Location Mechanisms on Discrete Trees

Reward Machines for Cooperative Multi-Agent Reinforcement Learning

Accumulating Risk Capital Through Investing in Cooperation

Timely Information from Prediction Markets

poster

https://assets.underline.io/transcript/12191/subtitle/34563a6dc708dbbab98bf416c2eb186f.vtt

English (automatic)

Mechanism Design Powered by Social Interactions (Blue Sky Ideas Track)

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