26 citations · 43 across the 25 of their papers we have counts for
5 papers · 1 filter
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…
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…
Enhancing Lifelong Multi-Agent Path-finding by Using Artificial Potential Fields
Arseniy Pertzovsky, Roni Stern, Ariel Felner +1
We explore the use of Artificial Potential Fields (APFs) to solve Multi-Agent Path Finding (MAPF) and Lifelong MAPF (LMAPF) problems. In MAPF, a team of agents must move to their g…
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…
Integrating Reinforcement Learning, Action Model Learning, and Numeric Planning for Tackling Complex Tasks
Yarin Benyamin, Argaman Mordoch, Shahaf S. Shperberg +1
Automated Planning algorithms require a model of the domain that specifies the preconditions and effects of each action. Obtaining such a domain model is notoriously hard. Algorith…