A Formal Theory of Optimal Learning with Experimental Results

Bennett, Michael Timothy

doi:10.24963/ijcai.2025/1238

A Formal Theory of Optimal Learning with Experimental Results

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Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence. Doctoral Consortium. Pages 10967-10968.

https://doi.org/10.24963/ijcai.2025/1238

Keywords

Search: S: Search and machine learning
Planning and Scheduling: PS: Other
Constraint Satisfaction and Optimization: CSO: Other
Search: S: Other
Machine Learning: ML: Learning theory

Abstract

Here I summarise some results from my thesis which are relevant to artificial intelligence (AI) and machine learning (ML). The key contribution is a theory of optimally sample and energy efficient learning, which is supported by mathematical proofs and experimental results.

Michael Timothy Bennett. 2025. A Formal Theory of Optimal Learning with Experimental Results. In Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25. IJCAI, 10967–10968. https://doi.org/10.24963/ijcai.2025/1238

@inproceedings{ijcai2025p1238,
  title     = {A Formal Theory of Optimal Learning with Experimental Results},
  author    = {Bennett, Michael Timothy},
  booktitle = {Proceedings of the Thirty-Fourth International Joint Conference on
               Artificial Intelligence, {IJCAI-25}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {James Kwok},
  pages     = {10967--10968},
  year      = {2025},
  month     = {8},
  note      = {Doctoral Consortium},
  doi       = {10.24963/ijcai.2025/1238},
  url       = {https://doi.org/10.24963/ijcai.2025/1238},
}

TY  - CPAPER
TI  - A Formal Theory of Optimal Learning with Experimental Results
AU  - Bennett, Michael Timothy
T2  - Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2025
SP  - 10967
EP  - 10968
DO  - 10.24963/ijcai.2025/1238
UR  - https://doi.org/10.24963/ijcai.2025/1238
ER  -