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  4. Online Planning in Stochastic Temporal Domains with Concurrent Actions

Online Planning in Stochastic Temporal Domains with Concurrent Actions

Ronan Brafman
  • 10Feb
    11:00 10th February 2026 ( week 4, Hilary Term 2026 )
    Bill Roscoe Room
Stochastic planning problems are typically modeled as Markov Decision Processes, in which actions are assumed to be instantaneous and applied sequentially. Yet, real-world actions often have durations and are applied concurrently. I will present an online planning approach that can deal with durative actions with stochastic outcomes. Our algorithm combines ideas from online MDP planning and classical temporal planning. We augment Monte Carlo Tree Search with a new backpropagation procedure and temporal reasoning techniques to address the need to both choose which action to execute and when to execute it. Beyond greater scalability, our planner can also problems unsolvable by prior methods due to greater flexibility in action timing.

Speaker bio

Ronen I. Brafman is a professor of Computer Science at Ben-Gurion University of the Negev. He received his Ph.D. from Stanford University, was a postdoctoral fellow at the University of British Columba, and a research scientist at NASA Ames Research Center. His research focuses on automated planning and decision making, especially under uncertainty and in multi-agent systems, and its application to robotics. He is a AAAI and Eur-AI fellow.

 

 

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