Inferring and Conveying Intentionality: Beyond Numerical Rewards to Logical Intentions

Susmit Jha and John Rushby

Presented at TOCAIS 2019: Towards Conscious AI Systems Symposium (part of AAAI SSS-19), Stanford CA, March 25-27, 2019


Shared intentionality is a critical component in developing conscious AI agents capable of collaboration, self-reflection, deliberation, and reasoning. We formulate inference of shared intentionality as an inverse reinforcement learning problem with logical reward specifications. We show how the approach can infer task descriptions from demonstrations. We also extend our approach to actively convey intentionality. We demonstrate the approach on a simple grid-world example.

Proceedings, and our paper (pdf), also available as arXiv 2207.05058

BibTeX Entry

	AUTHOR = {Susmit Jha and John Rushby},
	TITLE = {Inferring and Conveying Intentionality: Beyond Numerical
		Rewards to Logical Intentions},
	BOOKTITLE = {Towards Conscious AI Systems Symposium (TOCAIS):
		AAAI Spring Symposium Series},
	YEAR = 2019,
	EDITOR = {Antonio Chella and others},
	ADDRESS = {Stanford, CA},
	MONTH = mar

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