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Submit a Manuscript to the Journal
Advanced Robotics

For a Special Issue on
World Models and Predictive Coding in Robotics

Manuscript deadline
31 July 2022

Cover image - Advanced Robotics

Special Issue Editor(s)

Tadahiro Taniguchi, Ritsumeikan University, Japan
[email protected]

Dimitri Ognibene, Università Milano-Bicocca, Italy

Lorenzo Jamone, Queen Mary University of London, UK

Emre Ugur, Bogazici University, Turkey

Pablo Lanillos, Donders Institute for Brain, Cognition and Behaviour, Netherlands

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World Models and Predictive Coding in Robotics

Guest Editors (continued):

Alejandra Ciria (National Autonomous University of Mexico, Mexico)

Masahiro Suzuki (The University of Tokyo, Japan)

Shingo Murata (Keio University, Japan)

Yoshihiro Nakata (The University of Electro-Communications、Japan)

Tomoaki Nakamura (The University of Electro-Communications, Japan)

Developing autonomous cognitive-developmental robots is one of the dreams of robotics. An autonomous cognitive system should be able to learn and adapt to its environment through interactions. Importantly, the experience is based on its sensorimotor systems. Creating cognitive dynamics that allow a robot to develop and learn based on the robot's own action and perception cycles is a critical challenge in cognitive and developmental robotics. The autonomous learning process that occurs throughout development is also referred to as lifelong learning, and it is thought to be the foundation for the development of social capabilities necessary for adaptive collaborative robots.

Based on outstanding success in deep learning and probabilistic generative models in the 2010s, world models are attracting attention in artificial intelligence. A cognitive system (e.g., an agent) that learns a world model, with itself included, will be capable of predicting its future sensory observations and to optimize its controller (i.e., behavior) based on the prediction of the sensory consequences of its actions. The idea is closely related to predictive coding that has been studied in neurorobotics to develop neuro-dynamics realizing adaptive behaviors and social perception. Predictive coding and world models also share the same fundamental idea with the free-energy principle which is an influential theory in neuroscience nowadays.

Although the world model-based approach is promising in robotics, the many applications and studies of world models tend to be limited to simulation studies. The problems and challenges of developing autonomous cognitive-developmental robots based on world models, predictive coding, and the free-energy principle have not been fully explored on real and situated robots. These approaches are based on a generative view of cognition. In studies about cognitive development and symbol emergence in robotics, many computational cognitive models based on probabilistic generative models have been developed.

Therefore, this special issue focuses on the new frontiers in robotics, emphasizing world models, predictive coding, probabilistic generative models, and the free-energy principle. Papers on recent achievements in cognitive robotics are welcome. We also welcome surveys and short papers that clarify current essential topics in symbol emergence in robotics, cognitive robotics, and artificial intelligence. Prospective contributed papers are invited to cover, but are not limited to, the following topics:

  • World models for robotics
  • Predictive coding
  • A free-energy principle in robotics
  • Probabilistic generative models for robotics
  • Reinforcement learning with partial observations
  • Representation learning for robotics
  • Active inference and exploration for robotics
  • Whole-brain probabilistic generative models
  • Cognitive development and symbol emergence in robotics
  • Neuro/brain-inspired cognitive systems for robotic
  • Software frameworks for the application of world models and predictive coding in robotics
  • Cognitive architectures for robots
  • Symbol emergence with world modeling and predictive coding
  • Model based intention prediction in robotics
  • Adaptive world and agents models for social robotics

Submission Instructions

The full-length manuscript (either PDF or Microsoft Word file) should be sent to the office of Advanced Robotics, Robotics Society of Japan, through its homepage at: https://www.rsj.or.jp/pub/ar/submission.html. Templates for the manuscript and instructions for the authors are available on the homepage.

  •  Select "World Models and Predictive Coding in Robotics” when submitting your paper to ScholarOne
  •  Expected publication dates: May 2023 (Advanced Robotics vol. 37, Issue 9)

Instructions for AuthorsSubmit an Article

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