Anders Jonsson

research

∙ 01/26/2023

Generalized Planning as Heuristic Search: A new planning search-space that leverages pointers over objects

Planning as heuristic search is one of the most successful approaches to...

0 Javier Segovia-Aguas, et al. ∙

research

∙ 10/14/2022

Understanding Multi-link Operation in Wi-Fi 7: Performance, Anomalies, and Solutions

Will Wi-Fi 7, conceived to support extremely high throughput, also deliv...

0 Marc Carrascosa-Zamacois, et al. ∙

research

∙ 05/31/2022

Hierarchies of Reward Machines

Reward machines (RMs) are a recent formalism for representing the reward...

0 Daniel Furelos-Blanco, et al. ∙

research

∙ 05/30/2022

Performance and Coexistence Evaluation of IEEE 802.11be Multi-link Operation

Wi-Fi 7 is already in the making, and Multi-Link Operation (MLO) is one ...

0 Marc Carrascosa-Zamacois, et al. ∙

research

∙ 05/12/2022

Computing Programs for Generalized Planning as Heuristic Search

Although heuristic search is one of the most successful approaches to cl...

0 Javier Segovia-Aguas, et al. ∙

research

∙ 05/10/2022

Scaling-up Generalized Planning as Heuristic Search with Landmarks

Landmarks are one of the most effective search heuristics for classical ...

0 Javier Segovia-Aguas, et al. ∙

research

∙ 05/04/2022

State Representation Learning for Goal-Conditioned Reinforcement Learning

This paper presents a novel state representation for reward-free Markov ...

0 Lorenzo Steccanella, et al. ∙

research

∙ 06/03/2021

Hierarchical Representation Learning for Markov Decision Processes

In this paper we present a novel method for learning hierarchical repres...

0 Lorenzo Steccanella, et al. ∙

research

∙ 03/26/2021

Generalized Planning as Heuristic Search

Although heuristic search is one of the most successful approaches to cl...

0 Javier Segovia-Aguas, et al. ∙

research

∙ 01/15/2021

Hierarchical Width-Based Planning and Learning

Width-based search methods have demonstrated state-of-the-art performanc...

52 Miquel Junyent, et al. ∙

research

∙ 11/12/2020

Hierarchical reinforcement learning for efficient exploration and transfer

Sparse-reward domains are challenging for reinforcement learning algorit...

0 Lorenzo Steccanella, et al. ∙

research

∙ 09/09/2020

Improved Exploration in Factored Average-Reward MDPs

We consider a regret minimization task under the average-reward criterio...

0 Mohammad Sadegh Talebi, et al. ∙

research

∙ 09/08/2020

Induction and Exploitation of Subgoal Automata for Reinforcement Learning

In this paper we present ISA, an approach for learning and exploiting su...

0 Daniel Furelos-Blanco, et al. ∙

research

∙ 07/27/2020

Fast active learning for pure exploration in reinforcement learning

Realistic environments often provide agents with very limited feedback. ...

10 Pierre Ménard, et al. ∙

research

∙ 06/11/2020

Adaptive Reward-Free Exploration

Reward-free exploration is a reinforcement learning setting recently stu...

3 Emilie Kaufmann, et al. ∙

research

∙ 06/10/2020

Planning in Markov Decision Processes with Gap-Dependent Sample Complexity

We propose MDP-GapE, a new trajectory-based Monte-Carlo Tree Search algo...

10 Anders Jonsson, et al. ∙

research

∙ 05/17/2020

Usage of Network Simulators in Machine-Learning-Assisted 5G/6G Networks

Without any doubt, Machine Learning (ML) will be an important driver of ...

0 Francesc Wilhelmi, et al. ∙

research

∙ 05/16/2020

Lifelong Control of Off-grid Microgrid with Model Based Reinforcement Learning

The lifelong control problem of an off-grid microgrid is composed of two...

0 Simone Totaro, et al. ∙

research

∙ 11/29/2019

Induction of Subgoal Automata for Reinforcement Learning

In this work we present ISA, a novel approach for learning and exploitin...

0 Daniel Furelos-Blanco, et al. ∙

research

∙ 11/21/2019

Generalized Planning with Positive and Negative Examples

Generalized planning aims at computing an algorithm-like structure (gene...

0 Javier Segovia-Aguas, et al. ∙

research

∙ 11/07/2019

Hierarchical Finite State Controllers for Generalized Planning

Finite State Controllers (FSCs) are an effective way to represent sequen...

0 Javier Segovia-Aguas, et al. ∙

research

∙ 10/11/2019

Generalized Planning With Procedural Domain Control Knowledge

Generalized planning is the task of generating a single solution that is...

0 Javier Segovia-Aguas, et al. ∙

research

∙ 10/08/2019

A Flexible Machine Learning-Aware Architecture for Future WLANs

Lots of hopes have been placed in Machine Learning (ML) as a key enabler...

0 Francesc Wilhelmi, et al. ∙

research

∙ 10/08/2019

A Flexible Machine Learning-Aware Architecturefor Future WLANs

Lots of hopes have been placed in Machine Learning (ML) as a key enabler...

0 Francesc Wilhelmi, et al. ∙

research

∙ 07/25/2019

Decision Tree Learning for Uncertain Clinical Measurements

Clinical decision requires reasoning in the presence of imperfect data. ...

0 Cecília Nunes, et al. ∙

research

∙ 06/19/2019

Solving Multiagent Planning Problems with Concurrent Conditional Effects

In this work we present a novel approach to solving concurrent multiagen...

0 Daniel Furelos-Blanco, et al. ∙

research

∙ 04/12/2019

Deep Policies for Width-Based Planning in Pixel Domains

Width-based planning has demonstrated great success in recent years due ...

0 Miquel Junyent, et al. ∙

research

∙ 06/15/2018

Improving width-based planning with compact policies

Optimal action selection in decision problems characterized by sparse, d...

0 Miquel Junyent, et al. ∙

research

∙ 06/07/2018

Assessing the impact of machine intelligence on human behaviour: an interdisciplinary endeavour

This document contains the outcome of the first Human behaviour and mach...

0 Emilia Gómez, et al. ∙

research

∙ 05/28/2018

Potential and Pitfalls of Multi-Armed Bandits for Decentralized Spatial Reuse in WLANs

Spatial Reuse (SR) has recently gained attention for performance maximiz...

0 Francesc Wilhelmi, et al. ∙

research

∙ 10/31/2017

Collaborative Spatial Reuse in Wireless Networks via Selfish Multi-Armed Bandits

Next-generation wireless deployments are characterized by being dense an...

0 Francesc Wilhelmi, et al. ∙

research

∙ 05/22/2017

A unified view of entropy-regularized Markov decision processes

We propose a general framework for entropy-regularized average-reward re...

0 Gergely Neu, et al. ∙

research

∙ 03/10/2016

Hierarchical Linearly-Solvable Markov Decision Problems

We present a hierarchical reinforcement learning framework that formulat...

0 Anders Jonsson, et al. ∙

research

∙ 01/15/2014

The Role of Macros in Tractable Planning

This paper presents several new tractability results for planning based ...

0 Anders Jonsson, et al. ∙

research

∙ 01/15/2014

Planning over Chain Causal Graphs for Variables with Domains of Size 5 Is NP-Hard

Recently, considerable focus has been given to the problem of determinin...

0 Omer Giménez, et al. ∙

research

∙ 10/31/2011

The Complexity of Planning Problems With Simple Causal Graphs

We present three new complexity results for classes of planning problems...

0 Omer Giménez, et al. ∙

Anders Jonsson

Featured Co-authors