Artificial intelligence has been integrated into our daily activity. We can find it in our smartphones, computers, voice assistants, cities, etc, ... However, most of these devices use the cloud to process and apply different AI techniques. This massive sending of information makes appear the limitations of working in the cloud, such as latency, excessive energy consumption, security and the cost of having a series of dedicated servers for this purpose. These limitations have created a bottleneck for implementing AI products and services in environments close to data sources. It is for these reasons that in recent years the idea of lowering AI has spread, coining the concept of EDGE AI. 

This workshop focuses on the challenges of disaggregating AI processing through the use of Agents and the EDGE AI paradigm, from devices located at the end of the network (IoT, Embedded Systems) to the cloud. Incorporating small machine learning models in battery-powered devices, the use of AI for network outage, the application of machine learning for data transmission, and the implementation of a cohesive infrastructure that allows developers to create AI software for the periphery. 

The objective of this workshop is to bring together researchers and professionals who conduct research related to Artificial Intelligence techniques in energy-efficient devices. We welcome any article on experiences related to the use of agents in edge devices. 

The AgEdAI workshop is a forum to share ideas, projects, research results, applications, experiences, etc. associated with EDGE AI-based solutions and multi-agent systems within the framework of the International Conference on Practical Applications of Agents and Multiagent Systems 2020 (PAAMS 2020). 


Topics that could be relevant for the workshop include specially applications, but also theoretical approaches, based on:

  • Edge AI and MAS 
  • Machine Learning on Edge AI 
  • Reinforcement Learning on Edge AI 
  • Multi Agent Learning based on Edge AI 
  • Edge AI in IoT applications 
  • Edge Ai in Healthcare 
  • Edge AI in Factory 4.0 
  • Edge AI in Smart Home 
  • Edge Ai in Smart Cities 
  • Edge AI in Agricultural Technology 
  • Edge AI Algorithms 
  • Real-Time Artificial Intelligence 


Organizing Committee

  • Jaime Andres Rincon Arango - Universitat Politècnica de València (Spain)
  • Vicente Julián - Universitat Politècnica de València (Spain)
  • Carlos Carrascosa - Universitat Politècnica de València (Spain)


Jaime Andrés Rincón Arango