[robotics-worldwide] [meetings] ICRA 2020 Workshop: "Towards Curious Robots: Modern Approaches for Intrinsically-Motivated Intelligent Behavior"

Chris Mavrogiannis cmavro at cs.washington.edu
Fri Mar 6 16:12:06 PST 2020


Call for Papers 

*************************************************************** 
ICRA 2020 Workshop "Towards Curious Robots: 
Modern Approaches for Intrinsically-Motivated Intelligent Behavior" 
*************************************************************** 
Key Facts: 
ICRA 2020 Workshop, Thursday June 4th, 2020 
Location: Palais des Congrès de Paris - FRANCE 

Submission Deadline:  April 5th,  2020 
Notification Due:     April 15th, 2020 

URL:
https://urldefense.proofpoint.com/v2/url?u=https-3A__sites.google.com_asu.edu_curiousrobots_&d=DwIFaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=u9cyruLu9C4P3zs9jx8RjNGUUqDedA1w7oQ-iyk3iig&s=YNPPivmGLsbvSoCLPyfQa0QxSrOGr82-DYHssROiZRY&e=  

Organizers: Heni Ben Amor, Soshi Iba, David Isele, Chris Mavrogiannis, 
Joshua Tenenbaum 
*************************************************************** 

================== 
Scope and Motivation 
================== 
Curiosity is widely recognized as a fundamental mode of cognition and is 
particularly critical during childhood development. As such, it drives 
children and adults alike towards novel, previously unseen objects, 
movements and other stimuli, yielding new information and insights about the 
world and its underlying processes. Developing intelligent robots with a 
sense of "curiosity" may lead to an important breakthrough in artificial 
intelligence: agents that proactively expand their knowledge and 
capabilities by themselves through a snowballing process of 
information-generation. Recent attempts in using curiosity-inspired 
approaches in reinforcement learning, robot perception, task and motion 
planning, human-robot interaction and other fields of AI, have generated 
remarkable results but are largely independent of each other. Hence, there 
is an increasing need for a better understanding of this phenomenon at a 
broader scale through the collaboration of a diverse set of researchers. 

In this workshop, we aim to bring together researchers, students and 
practitioners in robotics and other sciences to discuss how to build curious 
robots and agents. We invite both researchers developing tools to recreate 
aspects of intelligent agents, e.g., reinforcement learning, active 
learning, deep learning, symbolic reasoning, computer vision; as well as 
researchers in trying to understand intelligent agents, e.g., in biology, 
psychology, human-robot interaction. As an outcome of this workshop, we 
expect the participating researchers to identify and address important 
challenges, techniques, and benchmarks that are needed to better understand, 
model, synthesize and analyze curiosity-driven behavior in robots. More 
generally, the objective of the workshop is to better understand adaptation, 
learning, and planning in open-ended and evolving scenarios and tasks. 

=============== 
Important Dates 
=============== 
  
* April 5th 2020 - Deadline for paper submissions 
* April 15th 2020 - Notification 
* June 4th 2020 - Workshop 

=============== 
Workshop Format 
=============== 

A key goal of the workshop is to identify modern techniques for open-ended 
and curiosity-based adaptation, learning and planning by presenting novel 
technical contributions. Surveys of recent advances in the field are also 
welcome. In this manner, the current state-of-the-art can be assessed. 
Given these insights, we want to discuss important next steps and open 
problems in the field. 

Relevant topic areas include (but are not limited to): 

- Developmental robotics 
- Curiosity-driven learning 
- Self-supervised learning 
- Symbolic reasoning about novel objects 
- Open-ended approaches to robot programming 
- Curiosity for perception and attention 
- Formalizing the curiosity and the “hunger for knowledge” 
- Learning based on prediction errors 
- Cognitive origins of curiosity 
- Information-theoretic reward functions 
- Balancing intrinsic and extrinsic rewards 
- Goal and sub-goal generation processes 
- Reinforcement learning with intrinsic rewards 
- Curious behavior in social settings and human-robot interaction 

=============== 
Keynote Speakers 
=============== 

* Dr. Pierre-Yves Oudeyer (INRIA) - Confirmed 

* Prof. Siddhartha Srinivasa (University of Washington) - Confirmed 

* Prof. Nicholas Roy (Massachusetts Institute of Technology) - Confirmed 

* Prof. Kostas Daniilidis (University of Pennsylvania) - Confirmed 

========== 
Submission 
========== 

Prospective participants are invited to submit short papers of up to 4 
pages). 
The paper should be submitted in the format of IEEE/ICRA formatting 
guidelines.   

We aim to publish all papers on our website and as an Arxiv collection to 
enable 
easy access to the information. Depending on the overall quality of the 
contributions, 
we might consider proposing a journal Special Issue in the near future. All 
papers 
for the Workshop must be submitted in PDF format by email to the address: 

[hidden email] 
  
Submission is not anonymous. 

================= 
Workshop Organizers 
================= 

* Heni Ben Amor, Arizona State University 
* Soshi Iba, Honda Research Institute USA 
* David Isele, Honda Research Institute USA 
* Chris Mavrogiannis, University of Washington 
* Joshua Tenenbaum, Massachusetts Institute of Technology 



-----
Christoforos Mavrogiannis, Ph.D.
Postdoctoral Research Associate
Paul G. Allen School of Computer Science & Engineering
University of Washington
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