Spain

ECAI 2020

Robot self other distinction active inference meets neural networks learning in a mirror

AAMAS is the leading scientific conference for research in autonomous agents and multi-agent systems. The AAMAS conference series was initiated in 2002 as the merging of three respected scientific meetings: the International Conference on Multi-Agent Systems (ICMAS), the International Workshop on Agent Theories, Architectures, and Languages (ATAL), and the International Conference on Autonomous Agents (AA). The aim of the joint conference is to provide a single, high-profile, internationally-respected archival forum for scientific research in the theory and practice of autonomous agents and multi-agent systems.

Browse keynotes, discussions, panels and over 300 presentations.


AAMAS 2020

AAMAS is the leading scientific conference for research in autonomous agents and multi-agent systems. The AAMAS conference series was initiated in 2002 as the merging of three respected scientific meetings: the International Conference on Multi-Agent Systems (ICMAS), the International Workshop on Agent Theories, Architectures, and Languages (ATAL), and the International Conference on Autonomous Agents (AA). 

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.

Minimality of Combined Qualitative Constraint Networks

SI-AGAN: Spatial Interpolation with Attentional Generative Adversarial Networks for Environment Monitoring

You Shouldn’t Trust Me: Learning Models Which Conceal Unfairness From Multiple Explanation Methods

Maximal Correlation: An Alternative Criterion for Training Generative Networks

Automated Verification of Social Law Robustness for Reactive Agents

Common and Discriminative Semantic Pursuit for Multi-modal Multi-label Learning

ST-MFM: A Spatiotemporal Multi-modal Fusion Model for Urban Anomalies Prediction

Homogeneous Online Transfer Learning with Online Distribution Discrepancy Minimization

Semantic Point Completion Network for 3D Semantic Scene Completion

Learning Class-based Graph Representation for Object Detection

https://d3smihljt9218e.cloudfront.net/transcript/1767/subtitle/08a31a7372acbeda87f0bca4b5048f6f.vtt

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Robot self other distinction active inference meets neural networks learning in a mirror

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Minimality of Combined Qualitative Constraint Networks

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Robot self other distinction active inference meets neural networks learning in a mirror

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Next from ECAI 2020

Minimality of Combined Qualitative Constraint Networks

Similar lecture

Optimal Swarm Strategy for Dynamic Target Search and Tracking

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