Spain

ECAI 2020

Auction Description Language (ADL): a General Framework for Representing Auction-based Markets

auction-based markets

general game playing

game description language

logics for multi-agents

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

Registration Is Required

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).

technical paper

ECAI2020 featured a full programme of technical papers, as well as many AI-related events of interest for researchers, students and all attendants who are interested on contemporary AI, including:




**An extensive programme of workshops, tutorials, and invited speakers**

**The Prestigious Applications of Intelligent Systems conference (PAIS)**

**The Frontiers in AI track sessions**

**The Lab To Market event**

**The Women in AI time**

**The EU Challenges forum**

… and many more!

ECAI 2020 featured a full programme of technical papers, as well as many AI-related events of interest for researchers, students and all attendants who are interested on contemporary AI.

Comparing Topic-Aware Neural Networks for Bias Detection of News

The Last Voting Rule Is Home: Complexity of Control by Partition of Candidates or Voters in Maximin Elections.

Verification of Neural Networks: Enhancing Scalability through Pruning

Integrating Open-Ended Learning in the Sense-Plan-Act Robot Control Paradigm

Applying the Closed World Assumption to SUMO-based FOL Ontologies for Effective Commonsense Reasoning

Group Behavior Recognition Using Attention- and Graph-Based Neural Networks

How Much Knowledge is in a Knowledge Base? Introducing Knowledge Measures (Preliminary Report)

Human Activity Recognition from Wearable Sensor Data Using Self-Attention

Learning Temporal Action Models via Constraint Programming

Finite and Con dent Teaching in Expectation: Sampling from In finite Concept Classes

https://d3smihljt9218e.cloudfront.net/transcript/1082/subtitle/ee4a03373abddfc3d774f36eccc17bb3.vtt

English (automatic)

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Comparing Topic-Aware Neural Networks for Bias Detection of News

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Comparing Topic-Aware Neural Networks for Bias Detection of News

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A Graph Neural Network Reasoner for Game Description Language

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