Search Results for author: Daniel Borrajo

Found 25 papers, 1 papers with code

Shining a Light on Hurricane Damage Estimation via Nighttime Light Data: Pre-processing Matters

no code implementations29 Oct 2024 Nancy Thomas, Saba Rahimi, Annita Vapsi, Cathy Ansell, Elizabeth Christie, Daniel Borrajo, Tucker Balch, Manuela Veloso

Amidst escalating climate change, hurricanes are inflicting severe socioeconomic impacts, marked by heightened economic losses and increased displacement.

Imputation

Enabling Advanced Land Cover Analytics: An Integrated Data Extraction Pipeline for Predictive Modeling with the Dynamic World Dataset

1 code implementation11 Oct 2024 Victor Radermecker, Andrea Zanon, Nancy Thomas, Annita Vapsi, Saba Rahimi, Rama Ramakrishnan, Daniel Borrajo

Understanding land cover holds considerable potential for a myriad of practical applications, particularly as data accessibility transitions from being exclusive to governmental and commercial entities to now including the broader research community.

On Learning Action Costs from Input Plans

no code implementations20 Aug 2024 Marianela Morales, Alberto Pozanco, Giuseppe Canonaco, Sriram Gopalakrishnan, Daniel Borrajo, Manuela Veloso

Most of the work on learning action models focus on learning the actions' dynamics from input plans.

valid

TRIP-PAL: Travel Planning with Guarantees by Combining Large Language Models and Automated Planners

no code implementations14 Jun 2024 Tomas De la Rosa, Sriram Gopalakrishnan, Alberto Pozanco, Zhen Zeng, Daniel Borrajo

Travel planning is a complex task that involves generating a sequence of actions related to visiting places subject to constraints and maximizing some user satisfaction criteria.

Language Modelling Large Language Model +1

Predicting Customer Goals in Financial Institution Services: A Data-Driven LSTM Approach

no code implementations22 May 2024 Andrew Estornell, Stylianos Loukas Vasileiou, William Yeoh, Daniel Borrajo, Rui Silva

In today's competitive financial landscape, understanding and anticipating customer goals is crucial for institutions to deliver a personalized and optimized user experience.

On the Sample Efficiency of Abstractions and Potential-Based Reward Shaping in Reinforcement Learning

no code implementations11 Apr 2024 Giuseppe Canonaco, Leo Ardon, Alberto Pozanco, Daniel Borrajo

The use of Potential Based Reward Shaping (PBRS) has shown great promise in the ongoing research effort to tackle sample inefficiency in Reinforcement Learning (RL).

Reinforcement Learning (RL)

Intelligent Execution through Plan Analysis

no code implementations18 Mar 2024 Daniel Borrajo, Manuela Veloso

Intelligent robots need to generate and execute plans.

Computer User Interface Understanding. A New Dataset and a Learning Framework

no code implementations15 Mar 2024 Andrés Muñoz, Daniel Borrajo

We also present a framework that is composed of a synthetic sample generation pipeline to augment the dataset with relevant characteristics, and a contrastive learning method to classify images in the videos.

Contrastive Learning

Methods for Matching English Language Addresses

no code implementations14 Mar 2024 Keshav Ramani, Daniel Borrajo

Addresses occupy a niche location within the landscape of textual data, due to the positional importance carried by every word, and the geographical scope it refers to.

Entity Resolution

On Computing Plans with Uniform Action Costs

no code implementations15 Feb 2024 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.

Generalising Planning Environment Redesign

no code implementations12 Feb 2024 Alberto Pozanco, Ramon Fraga Pereira, Daniel Borrajo

Most research on planning environment (re)design assumes the interested party's objective is to facilitate the recognition of goals and plans, and search over the space of environment modifications to find the minimal set of changes that simplify those tasks and optimise a particular metric.

Classification of Tabular Data by Text Processing

no code implementations21 Nov 2023 Keshav Ramani, Daniel Borrajo

Natural Language Processing technology has advanced vastly in the past decade.

Classification

Contrastive Explanations of Centralized Multi-agent Optimization Solutions

no code implementations11 Aug 2023 Parisa Zehtabi, Alberto Pozanco, Ayala Bloch, Daniel Borrajo, Sarit Kraus

We propose CMAoE, a domain-independent approach to obtain contrastive explanations by: (i) generating a new solution $S^\prime$ where property $P$ is enforced, while also minimizing the differences between $S$ and $S^\prime$; and (ii) highlighting the differences between the two solutions, with respect to the features of the objective function of the multi-agent system.

Fairness in Multi-Agent Planning

no code implementations1 Dec 2022 Alberto Pozanco, Daniel Borrajo

In cooperative Multi-Agent Planning (MAP), a set of goals has to be achieved by a set of agents.

Fairness

Inapplicable Actions Learning for Knowledge Transfer in Reinforcement Learning

no code implementations28 Nov 2022 Leo Ardon, Alberto Pozanco, Daniel Borrajo, Sumitra Ganesh

Knowing this information can help reduce the sample complexity of RL algorithms by masking the inapplicable actions from the policy distribution to only explore actions relevant to finding an optimal policy.

reinforcement-learning Reinforcement Learning +2

Anticipatory Counterplanning

no code implementations30 Mar 2022 Alberto Pozanco, Yolanda E-Martín, Susana Fernández, Daniel Borrajo

In competitive environments, commonly agents try to prevent opponents from achieving their goals.

Advising Agent for Service-Providing Live-Chat Operators

no code implementations9 May 2021 Aviram Aviv, Yaniv Oshrat, Samuel A. Assefa, Tobi Mustapha, Daniel Borrajo, Manuela Veloso, Sarit Kraus

Call centers, in which human operators attend clients using textual chat, are very common in modern e-commerce.

Goal recognition via model-based and model-free techniques

no code implementations3 Nov 2020 Daniel Borrajo, Sriram Gopalakrishnan, Vamsi K. Potluru

In this paper, we adapt state-of-the-art learning techniques to goal recognition, and compare model-based and model-free approaches in different domains.

Simulating and classifying behavior in adversarial environments based on action-state traces: an application to money laundering

no code implementations3 Nov 2020 Daniel Borrajo, Manuela Veloso, Sameena Shah

One of the key characteristics of these applications is the wide range of strategies that an adversary may choose as they adapt their strategy dynamically to sustain benefits and evade authorities.

Guarantees for Sound Abstractions for Generalized Planning (Extended Paper)

no code implementations28 May 2019 Blai Bonet, Raquel Fuentetaja, Yolanda E-Martin, Daniel Borrajo

Recently it has been shown how to reduce the planning problem for generalized planning to the planning problem for a qualitative numerical problem; the latter being a reformulation that simultaneously captures all the instances in the collection.

Error Analysis and Correction for Weighted A*'s Suboptimality (Extended Version)

no code implementations27 May 2019 Robert C. Holte, Ruben Majadas, Alberto Pozanco, Daniel Borrajo

There is broad consensus that this bound is not very accurate, that the actual suboptimality of wA*'s solution is often much less than W times optimal.

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