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1. Safe Space Commitment

   https://doi.org/10.5670/oceanog.2024.118  

   Pedra_Nobre, Rosana; Caref, Elisa; Balladares, Elizabeth; Zaima-Sheehy, Laurel (January 2023, Oceanography)

   Many cities around the world are taking steps to celebrate urban nature and move toward more sustainable living. As we progress, there is increasing focus on environmental initiatives and on intersecting with Black, Indigenous, and people of color (BIPOC) and other marginalized communities. Because of the long history of racism in the conservation and environmental movements, BIPOC communities have often been excluded from working in environmental science, ecology, and related fields. According to one survey of more than 200 environmental nonprofits, government agencies, and funders, “People of color are 36% of the US population and comprise 29% of the science and engineering workforce but they do not exceed 16% of the staff in any of the organizations surveyed” (Green 2.0, 2021). Absent changes in the latter percentages, environmental organizations cannot effectively address many of the urban environmental issues they face without input from, and connection with, these communities. 

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2. Safe Permissionless Consensus

   Pu, Youer; Alvisi, Lorenzo; Eyal, Ittay (October 2022, Leibniz international proceedings in informatics)

   Scheideler, Christian (Ed.)

   Nakamoto’s consensus protocol works in a permissionless model, where nodes can join and leave without notice. However, it guarantees agreement only probabilistically. Is this weaker guarantee a necessary concession to the severe demands of supporting a permissionless model? This paper shows that, at least in a benign failure model, it is not. It presents Sandglass, the first permissionless con- sensus algorithm that guarantees deterministic agreement and termination with probability 1 under general omission failures. Like Nakamoto, Sandglass adopts a hybrid synchronous communication model, where, at all times, a majority of nodes (though their number is unknown) are correct and synchronously connected, and allows nodes to join and leave at any time. 

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3. Safe Explicable Planning

   https://doi.org/10.1609/icaps.v34i1.31482  

   Hanni, Akkamahadevi; Boateng, Andrew; Zhang, Yu (May 2024, Proceedings of the International Conference on Automated Planning and Scheduling)

   Human expectations arise from their understanding of others and the world. In the context of human-AI interaction, this understanding may not align with reality, leading to the AI agent failing to meet expectations and compromising team performance. Explicable planning, introduced as a method to bridge this gap, aims to reconcile human expectations with the agent's optimal behavior, facilitating interpretable decision-making. However, an unresolved critical issue is ensuring safety in explicable planning, as it could result in explicable behaviors that are unsafe. To address this, we propose Safe Explicable Planning (SEP), which extends the prior work to support the specification of a safety bound. The goal of SEP is to find behaviors that align with human expectations while adhering to the specified safety criterion. Our approach generalizes the consideration of multiple objectives stemming from multiple models rather than a single model, yielding a Pareto set of safe explicable policies. We present both an exact method, guaranteeing finding the Pareto set, and a more efficient greedy method that finds one of the policies in the Pareto set. Additionally, we offer approximate solutions based on state aggregation to improve scalability. We provide formal proofs that validate the desired theoretical properties of these methods. Evaluation through simulations and physical robot experiments confirms the effectiveness of our approach for safe explicable planning. 

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4. Safe Permissionless Consensus

   Pu, Youer (August 2024, Cornell University)

   Nakamoto’s consensus protocol, known for operating in a permissionless model where nodes can join and leave without notice. However, it guarantees agreement only probabilistically. Is this weaker guarantee a necessary concession to the severe demands of supporting a permissionless model? This thesis shows that it is not with the Sandglass and Gorilla Sandglass protocols. Sandglass emerges as the first permissionless consensus algorithm that transcends Nakamoto’s probabilistic limitations by guaranteeing deterministic agreement and termination with probability 1, under general omission failures. It operates under a hybrid synchronous communication model, where, despite the unknown number and dynamic participation of nodes, a majority are consistently correct and synchronously connected. Further building on the framework of Sandglass, Gorilla Sandglass is the first Byzantine fault-tolerant consensus protocol that preserves deterministic agreement and termination with probability 1 within the same synchronous model adopted by Nakamoto. Gorilla addresses the limitations of Sandglass, which only tolerates benign failures, by extending its robustness to include Byzantine failures. We prove the correctness of Gorilla by mapping executions that would violate agreement or termination in Gorilla to executions in Sandglass, where we know such violations are impossible. Establishing termination proves particularly interesting, as the mapping requires reasoning about infinite executions and their probabilities 

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5. Safe Controller Synthesis With Tunable Input-to-State Safe Control Barrier Functions

   https://doi.org/10.1109/LCSYS.2021.3087443  

   Alan, Anil; Taylor, Andrew J.; He, Chaozhe R.; Orosz, Gabor; Ames, Aaron D. (January 2022, IEEE Control Systems Letters)

   null (Ed.)