4 papers
Where Common Knowledge Cannot Be Formed, Common Belief Can -- Planning with Multi-Agent Belief Using Group Justified Perspectives
Guang Hu, Tim Miller, Nir Lipovetzky
Epistemic planning is the sub-field of AI planning that focuses on changing knowledge and belief. It is important in both multi-agent domains where agents need to have knowledge/be…
Reassessing Collaborative Writing Theories and Frameworks in the Age of LLMs: What Still Applies and What We Must Leave Behind
Daisuke Yukita, Tim Miller, Joel Mackenzie
In this paper, we conduct a critical review of existing theories and frameworks on human-human collaborative writing to assess their relevance to the current human-AI paradigm in o…
Exploring Explainable Multi-agent MCTS-minimax Hybrids in Board Game Using Process Mining
Yiyu Qian, Tim Miller, Zheng Qian +1
Monte-Carlo Tree Search (MCTS) is a family of sampling-based search algorithms widely used for online planning in sequential decision-making domains and at the heart of many recent…
Supporting Data-Frame Dynamics in AI-assisted Decision Making
Chengbo Zheng, Tim Miller, Alina Bialkowski +2
High stakes decision-making often requires a continuous interplay between evolving evidence and shifting hypotheses, a dynamic that is not well supported by current AI decision sup…