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Home > Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 35 > No. 17: IAAI-21, EAAI-21, AAAI-21 Special Programs and Special Track

Towards a Unifying Framework for Formal Theories of Novelty

February 1, 2023

Authors

Terrance Boult

Univ. Colorado Colorado Springs


Przemyslaw Grabowicz

Univ. Massachusetts


Derek Prijatelj

University of Notre Dame


Roni Stern

PARC


Lawrence Holder

Washington State Univ.


Joshua Alspector

IDA/ITSD


Mohsen M. Jafarzadeh

University Of Colorado Colorado Springs


Toqueer Ahmad

University Of Colorado Colorado Springs


Akshay Dhamija

University of Colorado Colorado Springs


Chunchun Li

University Of Colorado Colorado Springs


Steve Cruz

University Of Colorado Colorado Springs


Abhinav Shrivastava

Univ. Maryland


Carl Vondrick

Columbia Univ.


Scheirer Walter

University of Notre Dame


Proceedings:

No. 17: IAAI-21, EAAI-21, AAAI-21 Special Programs and Special Track

Volume

Issue:

Proceedings of the AAAI Conference on Artificial Intelligence, 35

Track:

Senior Member Presentation: Blue Sky Papers

Downloads:

Download PDF

Abstract:

Managing inputs that are novel, unknown, or out-of-distribution is critical as an agent moves from the lab to the open world. Novelty-related problems include being tolerant to novel perturbations of the normal input, detecting when the input includes novel items, and adapting to novel inputs. While significant research has been undertaken in these areas, a noticeable gap exists in the lack of a formalized definition of novelty that transcends problem domains. As a team of researchers spanning multiple research groups and different domains, we have seen, first hand, the difficulties that arise from ill-specified novelty problems, as well as inconsistent definitions and terminology. Therefore, we present the first unified framework for formal theories of novelty and use the framework to formally define a family of novelty types. Our framework can be applied across a wide range of domains, from symbolic AI to reinforcement learning, and beyond to open world image recognition. Thus, it can be used to help kick-start new research efforts and accelerate ongoing work on these important novelty-related problems.

DOI:

10.1609/aaai.v35i17.17766


AAAI

Proceedings of the AAAI Conference on Artificial Intelligence, 35



Topics: AAAI

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