Skip to main content

Comparative Reasoning for Intelligent Agents

  • Conference paper
  • First Online:
Artificial General Intelligence (AGI 2023)

Abstract

We demonstrate new comparative reasoning abilities of NARS, a formal model of intelligence, which enable the asymmetric comparison of perceivable quantifiable attributes of objects using relations. These new abilities are implemented by extending NAL with additional inference rules. We demonstrate the new capabilities in a bottle-picking experiment on a mobile robot running ONA, an implementation of NARS.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 64.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 84.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://github.com/opennars/OpenNARS-for-Applications.

References

  1. Bochkovskiy, A., Wang, C.Y., Liao, H.Y.M.: YOLOv4: optimal speed and accuracy of object detection. arXiv preprint arXiv:2004.10934 (2020)

  2. Chella, A.: A cognitive architecture for music perception exploiting conceptual spaces. In: Zenker, F., Gärdenfors, P. (eds.) Applications of Conceptual Spaces. SL, vol. 359, pp. 187–203. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-15021-5_10

    Chapter  Google Scholar 

  3. Chella, A., Dindo, H., Infantino, I.: Imitation learning and anchoring through conceptual spaces. Appl. AI 21(4–5), 343–359 (2007)

    Google Scholar 

  4. Chella, A., Frixione, M., Gaglio, S.: Conceptual spaces for computer vision representations. Artif. Intell. Rev. 16, 137–152 (2001). https://doi.org/10.1023/A:1011658027344

    Article  MATH  Google Scholar 

  5. Gardenfors, P.: Conceptual Spaces: The Geometry of Thought. MIT Press, Cambridge (2004)

    Google Scholar 

  6. Hammer, P., Isaev, P., Lofthouse, T., Johansson, R.: ONA for autonomous ROS-based robots. In: Goertzel, B., Iklé, M., Potapov, A., Ponomaryov, D. (eds.) AGI 2022. LNCS (LNAI), vol. 13539, pp. 231–242. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-19907-3_22

    Chapter  Google Scholar 

  7. Hammer, P., Lofthouse, T.: ‘OpenNARS for applications’: architecture and control. In: Goertzel, B., Panov, A.I., Potapov, A., Yampolskiy, R. (eds.) AGI 2020. LNCS (LNAI), vol. 12177, pp. 193–204. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-52152-3_20

    Chapter  Google Scholar 

  8. Latapie, H., Kilic, O., Thórisson, K.R., Wang, P., Hammer, P.: Neurosymbolic systems of perception & cognition: the role of attention. Front. Psychol. 2105 (2022)

    Google Scholar 

  9. Lieto, A., Chella, A., Frixione, M.: Conceptual spaces for cognitive architectures: a lingua franca for different levels of representation. Biologically Inspired Cogn. Archit. 19, 1–9 (2017)

    Article  Google Scholar 

  10. Riley, D.A., Ring, K., Thomas, J.: The effect of stimulus comparison on discrimination learning and transposition. J. Comp. Physiol. Psychol. 53(5), 415 (1960)

    Article  Google Scholar 

  11. Santoro, A., et al.: A simple neural network module for relational reasoning. In: Advances in Neural Information Processing Systems, vol. 30 (2017)

    Google Scholar 

  12. Umari, H., Mukhopadhyay, S.: Autonomous robotic exploration based on multiple rapidly-exploring randomized trees. In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1396–1402. IEEE (2017)

    Google Scholar 

  13. Wang, P.: The interpretation of fuzziness. IEEE Trans. Syst. Man Cybern. B Cybern. 26(4), 321–326 (1996)

    Article  Google Scholar 

  14. Wang, P.: Recommendation based on personal preference. In: Zhang, Y., Kandel, A., Lin, T., Yao, Y. (eds.) Computational Web Intelligence: Intelligent Technology for Web Applications, pp. 101–115. World Scientific Publishing Company, Singapore (2004)

    Chapter  Google Scholar 

  15. Wang, P.: Rigid Flexibility: The Logic of Intelligence. Springer, Dordrecht (2006). https://doi.org/10.1007/1-4020-5045-3

    Book  MATH  Google Scholar 

  16. Wang, P.: Non-Axiomatic Logic: A Model of Intelligent Reasoning. World Scientific, Singapore (2013)

    Book  Google Scholar 

  17. Zambaldi, V., et al.: Relational deep reinforcement learning. arXiv preprint arXiv:1806.01830 (2018)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Patrick Hammer .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Hammer, P., Isaev, P., Latapie, H., Lanza, F., Chella, A., Wang, P. (2023). Comparative Reasoning for Intelligent Agents. In: Hammer, P., Alirezaie, M., Strannegård, C. (eds) Artificial General Intelligence. AGI 2023. Lecture Notes in Computer Science(), vol 13921. Springer, Cham. https://doi.org/10.1007/978-3-031-33469-6_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-33469-6_13

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-33468-9

  • Online ISBN: 978-3-031-33469-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics