11 papers
Privacy Preserving Multi Agent Path Finding
Rotem Lev Lehman, Roni Stern, Guy Shani
In the multi-agent path finding (MAPF) problem, a group of agents search in a graph for a path for each agent where no two paths collide. While in all applications of MAPF the agen…
RAMP: Hybrid DRL for Online Learning of Numeric Action Models
Yarin Benyamin, Argaman Mordoch, Shahaf S. Shperberg +1
Automated planning algorithms require an action model specifying the preconditions and effects of each action, but obtaining such a model is often hard. Learning action models from…
Budget Allocation Policies for Real-Time Multi-Agent Path Finding
Raz Beck, Roni Stern
Multi-Agent Path finding (MAPF) is the problem of finding paths for a set of agents such that each agent reaches its desired destination while avoiding collisions with the other ag…
EvoGPT: Leveraging LLM-Driven Seed Diversity to Improve Search-Based Test Suite Generation
Lior Broide, Roni Stern, Argaman Mordoch
Search-Based Software Testing (SBST) is a well-established approach for automated unit test generation, yet it often suffers from premature convergence and limited diversity in the…
Toward PDDL Planning Copilot
Yarin Benyamin, Argaman Mordoch, Shahaf S. Shperberg +1
Large Language Models (LLMs) are increasingly being used as autonomous agents capable of performing complicated tasks. However, they lack the ability to perform reliable long-horiz…
Learning Safe Numeric Planning Action Models
Argaman Mordoch, Shahaf S. Shperberg, Roni Stern +1
A significant challenge in applying planning technology to real-world problems lies in obtaining a planning model that accurately represents the problem's dynamics. Obtaining a pla…