2nd Workshop on Lifelong Learning: A Reinforcement Learning Approach @ICML/IJCAI 2018.
LLARLA 2018
- URL: https://sites.google.com/view/llarla2018/home
- Event Date: 2018-07-14 ~ 2018-07-15
- Submission Date: 2018-05-23
- Location: Stockholm, Sweden
Dear Colleagues,
We would like to invite you to submit extended abstracts of between 4-8 pages to our 'Lifelong Learning: A Reinforcement Learning Approach' ICML/IJCAI 2018 Workshop which will be held in Stockholm, Sweden on July 14 or 15, 2018. This workshop is part of the Federated AI Meeting (FAIM) which includes ICML/IJCAI/AAMAS/ICCBR.
IMPORTANT INFORMATION
************************************************
Website: https://sites.google.com/view/llarla2018/
Date: 14 or 15 July 2018
Location: Stockholm, Sweden
Submission deadline: 23rd May 2018, 11:59 PM (Anywhere on Earth)
OVERVIEW
************************************************
One of the most challenging and open problems in Artificial Intelligence (AI) is that of Lifelong Learning:
“Lifelong Learning is the continued learning of tasks, from one or more domains, over the course of a lifetime, by a lifelong learning system. A lifelong learning system efficiently and effectively (1) retains the knowledge it has learned; (2) selectively transfers knowledge to learn new tasks; and (3) ensures the effective and efficient interaction between (1) and (2).”
Lifelong learning is still in its infancy. Many issues currently exist such as learning general representations, catastrophic forgetting, efficient knowledge retention mechanisms and hierarchical abstractions. Much work has been done in the Reinforcement Learning (RL) community to tackle different elements of lifelong learning. Active research topics include hierarchical abstractions, transfer learning, multi-task learning and curriculum learning. With the emergence of powerful function approximators such as in Deep Learning, we feel that now is a perfect time to provide a forum to discuss ways to move forward and provide a truly general lifelong learning framework, using RL-based algorithms, with more rigor than ever before. This workshop will endeavor to promote interaction between researchers working on the different elements of lifelong learning to try and find a synergy between the various techniques.
SUBMISSION
************************************************
The submitted work should be an extended abstract of between 4-8 pages (including references). The submission should be in pdf format and should follow the style guidelines for ICML 2018. The review process is double-blind and the work should be submitted by the latest 23rd May 2018, 11:59 PM(Anywhere on Earth). Submissions must be made through easychair:
https://easychair.org/conferences/?conf=llarla2018
AREAS OF INTEREST
************************************************
Using Hierarchical Abstractions to perform lifelong learning (e.g., skills/options and state space representations)
Catastrophic forgetting in lifelong learning
Transfer Learning
Multi-task Learning
Curriculum Learning
Meta-Learning
Deep Learning as a tool for performing lifelong learning
Determine new, challenging benchmark domains
For more info see our website.
WORKSHOP ORGANIZERS
************************************************
Sarath Chandar - University of Montreal
Tom Zahavy - Technion Israel Institute of Technology
Daniel J. Mankowitz - Technion Israel Institute of Technology
Balaraman Ravindran - Indian Institute of Technology
Shie Mannor - Technion Israel Institute of Technology
We look forward to reviewing your submissions and hope to see you in Stockholm!
Kind regards,
Sarath, Tom, Daniel, Ravi, and Shie
Lifelong Learning: A Reinforcement Learning Approach Workshop organizers
We would like to invite you to submit extended abstracts of between 4-8 pages to our 'Lifelong Learning: A Reinforcement Learning Approach' ICML/IJCAI 2018 Workshop which will be held in Stockholm, Sweden on July 14 or 15, 2018. This workshop is part of the Federated AI Meeting (FAIM) which includes ICML/IJCAI/AAMAS/ICCBR.
IMPORTANT INFORMATION
************************************************
Website: https://sites.google.com/view/llarla2018/
Date: 14 or 15 July 2018
Location: Stockholm, Sweden
Submission deadline: 23rd May 2018, 11:59 PM (Anywhere on Earth)
OVERVIEW
************************************************
One of the most challenging and open problems in Artificial Intelligence (AI) is that of Lifelong Learning:
“Lifelong Learning is the continued learning of tasks, from one or more domains, over the course of a lifetime, by a lifelong learning system. A lifelong learning system efficiently and effectively (1) retains the knowledge it has learned; (2) selectively transfers knowledge to learn new tasks; and (3) ensures the effective and efficient interaction between (1) and (2).”
Lifelong learning is still in its infancy. Many issues currently exist such as learning general representations, catastrophic forgetting, efficient knowledge retention mechanisms and hierarchical abstractions. Much work has been done in the Reinforcement Learning (RL) community to tackle different elements of lifelong learning. Active research topics include hierarchical abstractions, transfer learning, multi-task learning and curriculum learning. With the emergence of powerful function approximators such as in Deep Learning, we feel that now is a perfect time to provide a forum to discuss ways to move forward and provide a truly general lifelong learning framework, using RL-based algorithms, with more rigor than ever before. This workshop will endeavor to promote interaction between researchers working on the different elements of lifelong learning to try and find a synergy between the various techniques.
SUBMISSION
************************************************
The submitted work should be an extended abstract of between 4-8 pages (including references). The submission should be in pdf format and should follow the style guidelines for ICML 2018. The review process is double-blind and the work should be submitted by the latest 23rd May 2018, 11:59 PM(Anywhere on Earth). Submissions must be made through easychair:
https://easychair.org/conferences/?conf=llarla2018
AREAS OF INTEREST
************************************************
Using Hierarchical Abstractions to perform lifelong learning (e.g., skills/options and state space representations)
Catastrophic forgetting in lifelong learning
Transfer Learning
Multi-task Learning
Curriculum Learning
Meta-Learning
Deep Learning as a tool for performing lifelong learning
Determine new, challenging benchmark domains
For more info see our website.
WORKSHOP ORGANIZERS
************************************************
Sarath Chandar - University of Montreal
Tom Zahavy - Technion Israel Institute of Technology
Daniel J. Mankowitz - Technion Israel Institute of Technology
Balaraman Ravindran - Indian Institute of Technology
Shie Mannor - Technion Israel Institute of Technology
We look forward to reviewing your submissions and hope to see you in Stockholm!
Kind regards,
Sarath, Tom, Daniel, Ravi, and Shie
Lifelong Learning: A Reinforcement Learning Approach Workshop organizers
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