World models and predictive coding for cognitive and developmental robotics: frontiers and challenges

Creating autonomous robots that can actively explore the environment, acquire knowledge and learn skills continuously is the ultimate achievement envisioned in cognitive and developmental robotics. Importantly, if the aim is to create robots that can continuously develop through interactions with th...

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Veröffentlicht in:Advanced robotics Jg. 37; H. 13; S. 780 - 806
Hauptverfasser: Taniguchi, Tadahiro, Murata, Shingo, Suzuki, Masahiro, Ognibene, Dimitri, Lanillos, Pablo, Ugur, Emre, Jamone, Lorenzo, Nakamura, Tomoaki, Ciria, Alejandra, Lara, Bruno, Pezzulo, Giovanni
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Taylor & Francis 03.07.2023
Schlagworte:
active inference
cognitive robotics
free-energy principle
predictive coding
World model
ISSN:0169-1864, 1568-5535
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Abstract Creating autonomous robots that can actively explore the environment, acquire knowledge and learn skills continuously is the ultimate achievement envisioned in cognitive and developmental robotics. Importantly, if the aim is to create robots that can continuously develop through interactions with their environment, their learning processes should be based on interactions with their physical and social world in the manner of human learning and cognitive development. Based on this context, in this paper, we focus on the two concepts of world models and predictive coding. Recently, world models have attracted renewed attention as a topic of considerable interest in artificial intelligence. Cognitive systems learn world models to better predict future sensory observations and optimize their policies, i.e. controllers. Alternatively, in neuroscience, predictive coding proposes that the brain continuously predicts its inputs and adapts to model its own dynamics and control behavior in its environment. Both ideas may be considered as underpinning the cognitive development of robots and humans capable of continual or lifelong learning. Although many studies have been conducted on predictive coding in cognitive robotics and neurorobotics, the relationship between world model-based approaches in AI and predictive coding in robotics has rarely been discussed. Therefore, in this paper, we clarify the definitions, relationships, and status of current research on these topics, as well as missing pieces of world models and predictive coding in conjunction with crucially related concepts such as the free-energy principle and active inference in the context of cognitive and developmental robotics. Furthermore, we outline the frontiers and challenges involved in world models and predictive coding toward the further integration of AI and robotics, as well as the creation of robots with real cognitive and developmental capabilities in the future.
AbstractList Creating autonomous robots that can actively explore the environment, acquire knowledge and learn skills continuously is the ultimate achievement envisioned in cognitive and developmental robotics. Importantly, if the aim is to create robots that can continuously develop through interactions with their environment, their learning processes should be based on interactions with their physical and social world in the manner of human learning and cognitive development. Based on this context, in this paper, we focus on the two concepts of world models and predictive coding. Recently, world models have attracted renewed attention as a topic of considerable interest in artificial intelligence. Cognitive systems learn world models to better predict future sensory observations and optimize their policies, i.e. controllers. Alternatively, in neuroscience, predictive coding proposes that the brain continuously predicts its inputs and adapts to model its own dynamics and control behavior in its environment. Both ideas may be considered as underpinning the cognitive development of robots and humans capable of continual or lifelong learning. Although many studies have been conducted on predictive coding in cognitive robotics and neurorobotics, the relationship between world model-based approaches in AI and predictive coding in robotics has rarely been discussed. Therefore, in this paper, we clarify the definitions, relationships, and status of current research on these topics, as well as missing pieces of world models and predictive coding in conjunction with crucially related concepts such as the free-energy principle and active inference in the context of cognitive and developmental robotics. Furthermore, we outline the frontiers and challenges involved in world models and predictive coding toward the further integration of AI and robotics, as well as the creation of robots with real cognitive and developmental capabilities in the future.
Author Murata, Shingo
Suzuki, Masahiro
Nakamura, Tomoaki
Ciria, Alejandra
Lara, Bruno
Ugur, Emre
Taniguchi, Tadahiro
Ognibene, Dimitri
Jamone, Lorenzo
Lanillos, Pablo
Pezzulo, Giovanni
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  surname: Taniguchi
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  orcidid: 0000-0002-0790-1915
  surname: Murata
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  givenname: Masahiro
  surname: Suzuki
  fullname: Suzuki, Masahiro
  organization: The University of Tokyo
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  surname: Ognibene
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  organization: University of Essex
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  surname: Lanillos
  fullname: Lanillos, Pablo
  organization: Spanish National Research Council
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  surname: Ugur
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  organization: Queen Mary University of London
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  organization: The University of Electro-Communications
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  givenname: Alejandra
  orcidid: 0000-0002-9216-9297
  surname: Ciria
  fullname: Ciria, Alejandra
  organization: National Autonomous University of Mexico
– sequence: 10
  givenname: Bruno
  orcidid: 0000-0002-9844-6435
  surname: Lara
  fullname: Lara, Bruno
  organization: Universidad Autónoma del Estado de Morelos
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  givenname: Giovanni
  orcidid: 0000-0001-6813-8282
  surname: Pezzulo
  fullname: Pezzulo, Giovanni
  organization: National Research Council of Italy
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Snippet Creating autonomous robots that can actively explore the environment, acquire knowledge and learn skills continuously is the ultimate achievement envisioned in...
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StartPage 780
SubjectTerms active inference
cognitive robotics
free-energy principle
predictive coding
World model
Title World models and predictive coding for cognitive and developmental robotics: frontiers and challenges
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