4 citations · 6 across the 9 of their papers we have counts for
9 papers
Reinforcement Learning with Reward Machines for Sleep Control in Mobile Networks
Kristina Levina, Nikolaos Pappas, Athanasios Karapantelakis +2
Energy efficiency in mobile networks is crucial for sustainable telecommunications infrastructure, particularly as network densification continues to increase power consumption. Sl…
Frontier Large Language Models Rival State-of-the-Art Planners
Augusto B. Corrêa, André G. Pereira, Jendrik Seipp
A series of influential studies established that large language models cannot reliably solve even simple planning tasks. We show that the latest generation of frontier models overt…
Symmetry-Aware Transformer Training for Automated Planning
Markus Fritzsche, Elliot Gestrin, Jendrik Seipp
While transformers excel in many settings, their application in the field of automated planning is limited. Prior work like PlanGPT, a state-of-the-art decoder-only transformer, st…
Classical Planning with LLM-Generated Heuristics: Challenging the State of the Art with Python Code
Augusto B. Corrêa, André G. Pereira, Jendrik Seipp
In recent years, large language models (LLMs) have shown remarkable capabilities in various artificial intelligence problems. However, they fail to plan reliably, even when prompte…
NL2Plan: Robust LLM-Driven Planning from Minimal Text Descriptions
Elliot Gestrin, Marco Kuhlmann, Jendrik Seipp
Classical planners are powerful systems, but modeling tasks in input formats such as PDDL is tedious and error-prone. In contrast, planning with Large Language Models (LLMs) allows…
Numeric Reward Machines
Kristina Levina, Nikolaos Pappas, Athanasios Karapantelakis +2
Reward machines inform reinforcement learning agents about the reward structure of the environment and often drastically speed up the learning process. However, reward machines onl…
Consolidating LAMA with Best-First Width Search
Augusto B. Corrêa, Jendrik Seipp
One key decision for heuristic search algorithms is how to balance exploration and exploitation. In classical planning, novelty search has come out as the most successful approach…
Learning Sketches for Decomposing Planning Problems into Subproblems of Bounded Width: Extended Version
Dominik Drexler, Jendrik Seipp, Hector Geffner
Recently, sketches have been introduced as a general language for representing the subgoal structure of instances drawn from the same domain. Sketches are collections of rules of t…
Expressing and Exploiting the Common Subgoal Structure of Classical Planning Domains Using Sketches: Extended Version
Dominik Drexler, Jendrik Seipp, Hector Geffner
Width-based planning methods deal with conjunctive goals by decomposing problems into subproblems of low width. Algorithms like SIW thus fail when the goal is not easily serializab…