8 citations · 10 across the 9 of their papers we have counts for
6 papers · 1 filter
TS-Agent: Understanding and Reasoning Over Raw Time Series via Iterative Insight Gathering
Penghang Liu, Elizabeth Fons, Annita Vapsi +5
Large language models (LLMs) exhibit strong symbolic and compositional reasoning, yet they struggle with time series question answering as the data is typically transformed into an…
The Subset Sum Matching Problem
Yufei Wu, Manuel R. Torres, Parisa Zehtabi +4
This paper presents a new combinatorial optimisation task, the Subset Sum Matching Problem (SSMP), which is an abstraction of common financial applications such as trades reconcili…
Planning with Minimal Disruption
Alberto Pozanco, Marianela Morales, Daniel Borrajo +1
In many planning applications, we might be interested in finding plans that minimally modify the initial state to achieve the goals. We refer to this concept as plan disruption. In…
A Planning Compilation to Reason about Goal Achievement at Planning Time
Alberto Pozanco, Marianela Morales, Daniel Borrajo +1
Identifying the specific actions that achieve goals when solving a planning task might be beneficial for various planning applications. Traditionally, this identification occurs po…
On Learning Action Costs from Input Plans
Marianela Morales, Alberto Pozanco, Giuseppe Canonaco +3
Most of the work on learning action models focus on learning the actions' dynamics from input plans. This allows us to specify the valid plans of a planning task. However, very lit…
On Computing Plans with Uniform Action Costs
Alberto Pozanco, Daniel Borrajo, Manuela Veloso
In many real-world planning applications, agents might be interested in finding plans whose actions have costs that are as uniform as possible. Such plans provide agents with a sen…