Spain

ECAI 2020

A Two-Stage Multi-Objective Deep Reinforcement Learning Framework

evolution strategy

pareto frontier

multi-objective reinforcement learning

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.

Online Probabilistic Interval-based Event Calculus

Saliency Detection with Deformable Convolution and Feature Attention

Non-Monotone Submodular Maximization with Multiple Knapsacks in Static and Dynamic Settings

Extended Markov Games to Learn Complex Specifications in Multi-Agent Reinforcement Learning

Efficient Neural Network Verification via Adaptive Refinement and Adversarial Search

Conference Presentation Recording for ECAI2020 paper 'Adaptive Graph Reasoning Network for Fashion Landmark Detection'

Feature-level Ensemble Knowledge Distillation for Aggregating Knowledge from Multiple Networks

Crowd Counting via Hierarchical Scale Recalibration Network

Learning a Latent Space of Style-Aware Symbolic Music Representations by Adversarial Autoencoders

Adaptive Local Neighbors for Transfer Discriminative Feature Learning

https://d3smihljt9218e.cloudfront.net/transcript/981/subtitle/241d8fd4d5e29981f511e8abcadbbfb0.vtt

English (automatic)

A Two-Stage Multi-Objective Deep Reinforcement Learning Framework

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Online Probabilistic Interval-based Event Calculus

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Multi-Objective Reinforcement Learning with Non-Linear Scalarization

A Two-Stage Multi-Objective Deep Reinforcement Learning Framework

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Next from ECAI 2020

Online Probabilistic Interval-based Event Calculus

Similar lecture

Multi-Objective Reinforcement Learning with Non-Linear Scalarization

Downloads