Toward Design of Synthetic Active Inference Agents by Mere Mortals

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Abstract

The theoretical properties of active inference agents are impressive, but how do we realize effective agents in working hardware and software on edge devices? This is an interesting problem because the computational load for policy exploration explodes exponentially, while the computational resources are very limited for edge devices. In this paper, we discuss the necessary features for a software toolbox that supports a competent non-expert engineer to develop working active inference agents. We introduce a toolbox-in-progress that aims to accelerate the democratization of active inference agents in a similar way as TensorFlow propelled applications of deep learning technology.
Original languageEnglish
Title of host publicationActive Inference
Subtitle of host publication4th International Workshop, IWAI 2023, Ghent, Belgium, September 13–15, 2023, Revised Selected Papers
EditorsChristopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Noor Sajid, Hideaki Shimazaki, Tim Verbelen, Martijn Wisse
Place of PublicationCham
PublisherSpringer
Pages173-185
Number of pages13
ISBN (Electronic)978-3-031-47958-8
ISBN (Print)978-3-031-47957-1
DOIs
Publication statusPublished - 2024
Event4th International Workshop on Active Inference, IWAI 2023 - Ghent, Belgium
Duration: 13 Sept 202315 Sept 2023

Publication series

NameCommunications in Computer and Information Science (CCIS)
Volume1915
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference4th International Workshop on Active Inference, IWAI 2023
Abbreviated titleIWAI 2023
Country/TerritoryBelgium
CityGhent
Period13/09/2315/09/23

Funding

I would like to acknowledge my colleagues at BIASlab (http:// biaslab.org) for the stimulating work environment and the anonymous reviewers for excellent feedback on the draft version. Some wording in this document, such as footnote (see footnote 2), comes straight from a reviewer.

Keywords

  • active inference agent
  • factor graphs
  • free energy minimization
  • reactive message passing
  • rxinfer
  • structural adaptation

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