Spain

ECAI 2020

Model-Free Non-Stationarity Detection and Adaptation in Reinforcement Learning

detection-adaptation approach for reinforcement learning

non-stationary reinforcement learning

reinforcement learning

AIAI 2020 (16th International Conference on Artificial Intelligence Applications and Innovations) should be held in Halkidiki, Greece. Due to current Covid-19 situation the conference will be held virtually. Underline will host a repository of video talks and preserve them for the future. Videos will be released on Underline one day after the conference.

AIAI 2020

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.

On-Time Delivery in Crowdshipping Systems: An Agent-Based Approach Using Streaming Data

Extending a Fuzzy Polarity Propagation Method for Multi-Domain Sentiment Analysis with Word Embedding and POS Tagging

Ludii - The Ludemic General Game System

Property Invariant Embedding for Automated Reasoning

An ideal team is more than a team of ideal agents

Deciding When, How and for Whom to Simplify

Knowledge Distillation for Model-Agnostic Meta-Learning

A Logic of Explicit and Implicit Distributed Belief

New randomized strategies for the color coding algorithm

MDE: Multiple Distance Embeddings for Link Prediction in Knowledge Graphs

https://d3smihljt9218e.cloudfront.net/transcript/1107/subtitle/b8790ae5dc5fe4ade2994b28e7bb8be4.vtt

English (automatic)

Model-Free Non-Stationarity Detection and Adaptation in Reinforcement Learning

Downloads

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On-Time Delivery in Crowdshipping Systems: An Agent-Based Approach Using Streaming Data

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Model-Free Non-Stationarity Detection and Adaptation in Reinforcement Learning

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Next from ECAI 2020

On-Time Delivery in Crowdshipping Systems: An Agent-Based Approach Using Streaming Data

Similar lecture

Deepbots: A Webots-based Deep Reinforcement Learning Framework for Robotics

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