Titlebook: Autonomous Agents and Multiagent Systems. Best and Visionary Papers; AAMAS 2022 Workshops Francisco S. Melo,Fei Fang Conference proceedings

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Enabling Negotiating Agents to?Explore Very Large Outcome Spacesgents from the Automated Negotiating Agents Competition. Furthermore, we validate one of our techniques by integrating it into negotiation platform GeniusWeb, to enable existing state-of-the-art agents (and future agents) to scale their use to very large outcome spaces.

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Only Those Who Can Obey Can Disobey: The Intentional Implications of?Artificial Agent Disobedience First, we attempt to disentangle figurative uses of the term “disobedience” from those connotative of deeper senses of agency. We then situate . disobedience as being committed by an agent through an action that presupposes some understanding of the violated instruction or command.

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School’s Out? Simulating Schooling Strategies During COVID-19n a population-level scale. To examine the impact of different schooling strategies, an agent-based model is used in the context of the COVID-19 pandemic using a German city as an example. The simulation experiments show that reducing the class size by rotating weekly between in-person classes and o

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Data-Driven Agent-Based Model Development to Support Human-Centric Transit-Oriented DesignTOD) designs and infrastructure investment proposals prepared by urban planners. The students test the model as model users, and the generated model output on the use of the city infrastructure, occupancy of public space, and key data around the pedestrian and vehicle movements can be translated to

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Enabling Negotiating Agents to?Explore Very Large Outcome SpacesDS provides a balance between being rapid, accurate, diverse, and scalable search, allowing agents to search spaces with as many as . possible outcomes on very run-of-the-mill hardware. We show that our algorithm can be used to respond to the three most common search queries employed by 87% of all a