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1. Partial Permutohedra

   Behrend, Roger E.; Castillo, Federico; Chavez, Anastasia; Diaz-Lopez, Alexander; Escobar, Laura; Harris, Pamela; Insko, Erik (April 2023, Séminaire lotharingien de combinatoire)
2. Partial Permutohedra

   Behrend, Roger E.; Castillo, Federico; Chavez, Anastasia; Diaz-Lopez, Alexander; Escobar, Laura; Harris, Pamela; Insko, Erik (April 2023, Séminaire lotharingien de combinatoire)
3. Partial awareness

   Halpern, Joseph Y.; Piermont, Evan (January 2019, Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence)

   We develop a modal logic to capture partial awareness. The logic has three building blocks: objects, properties, and concepts. Properties are unary predicates on objects; concepts are Boolean combinations of properties. We take an agent to be partially aware of a concept if she is aware of the concept without being aware of the properties that define it. The logic allows for quantification over objects and properties, so that the agent can reason about her own unawareness. We then apply the logic to contracts, which we view as syntactic objects that dictate outcomes based on the truth of formulas. We show that when agents are unaware of some relevant properties, referencing concepts that agents are only partially aware of can improve welfare. 

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4. Distributed Partial Clustering

   https://doi.org/10.1145/3322808  

   Guha, Sudipto; Li, Yi; Zhang, Qin (December 2019, ACM Transactions on Parallel Computing)
5. Dynamic partial awareness

   Halpern, J. Y.; Piermont, E. (September 2020, Proceedings of the Seventeenth International Conference on Principles of Knowledge Representation and Reasoning (KR 2020))

   null (Ed.)

   We investigate how to model the beliefs of an agent who becomes more aware. We use the framework of Halpern and R\^ego [2013], expanded by adding probability, and define a notion of a model transition that describes constraints on how, if an agent becomes aware of a new formula phi in state s of a model M, she transitions to state s* in a model M*. We then discuss how such a model can be applied to information disclosure. 

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