Francisco Cruz

Orcid: 0000-0002-1131-3382

Affiliations:
  • Deakin University, School of Information Technology, Geelong, Australia
  • University of Hamburg, Germany (former)
  • Universidad de Santiago de Chile (former)


According to our database1, Francisco Cruz authored at least 54 papers between 2007 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2024
Self context-aware emotion perception on human-robot interaction.
CoRR, 2024

2023
Persistent rule-based interactive reinforcement learning.
Neural Comput. Appl., November, 2023

Explainable robotic systems: understanding goal-driven actions in a reinforcement learning scenario.
Neural Comput. Appl., September, 2023

Human engagement providing evaluative and informative advice for interactive reinforcement learning.
Neural Comput. Appl., September, 2023

Proxemic behavior in navigation tasks using reinforcement learning.
Neural Comput. Appl., August, 2023

AI apology: interactive multi-objective reinforcement learning for human-aligned AI.
Neural Comput. Appl., August, 2023

Explainable reinforcement learning for broad-XAI: a conceptual framework and survey.
Neural Comput. Appl., August, 2023

Human-aligned reinforcement learning for autonomous agents and robots.
Neural Comput. Appl., August, 2023

Vessel Velocity Estimation and Docking Analysis: A Computer Vision Approach.
Algorithms, July, 2023

Editorial: Cognitive inspired aspects of robot learning.
Frontiers Neurorobotics, June, 2023

Towards a Broad-Persistent Advising Approach for Deep Interactive Reinforcement Learning in Robotic Environments.
Sensors, March, 2023

A conceptual framework for externally-influenced agents: an assisted reinforcement learning review.
J. Ambient Intell. Humaniz. Comput., 2023

Asch Meets HRI: Human Conformity to Robot Groups.
CoRR, 2023

Urban Autonomous Driving of Emergency Vehicles with Reinforcement Learning.
Proceedings of the IEEE Latin American Conference on Computational Intelligence, 2023

Time estimation for deep learning model's inference in distributed processing units.
Proceedings of the IEEE Latin American Conference on Computational Intelligence, 2023

Elastic step DDPG: Multi-step reinforcement learning for improved sample efficiency.
Proceedings of the International Joint Conference on Neural Networks, 2023

2022
Event-Based Angular Speed Measurement and Movement Monitoring.
Sensors, 2022

Introspection-based Explainable Reinforcement Learning in Episodic and Non-episodic Scenarios.
CoRR, 2022

Broad-persistent Advice for Interactive Reinforcement Learning Scenarios.
CoRR, 2022

Elastic Step DQN: A novel multi-step algorithm to alleviate overestimation in Deep QNetworks.
CoRR, 2022

Analysis of Explainable Goal-Driven Reinforcement Learning in a Continuous Simulated Environment.
Algorithms, 2022

Convolution Optimization in Fire Classification.
IEEE Access, 2022

Explaining Agent's Decision-making in a Hierarchical Reinforcement Learning Scenario.
Proceedings of the 41st International Conference of the Chilean Computer Science Society, 2022

Reinforcement Learning for UAV control with Policy and Reward Shaping.
Proceedings of the 41st International Conference of the Chilean Computer Science Society, 2022

Evaluating Human-like Explanations for Robot Actions in Reinforcement Learning Scenarios.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

2021
A Broad-persistent Advising Approach for Deep Interactive Reinforcement Learning in Robotic Environments.
CoRR, 2021

Explainable Deep Reinforcement Learning Using Introspection in a Non-episodic Task.
CoRR, 2021

Learning Proxemic Behavior Using Reinforcement Learning with Cognitive Agents.
CoRR, 2021

Levels of explainable artificial intelligence for human-aligned conversational explanations.
Artif. Intell., 2021

A Robust Approach for Continuous Interactive Actor-Critic Algorithms.
IEEE Access, 2021

2020
Deep Reinforcement Learning with Interactive Feedback in a Human-Robot Environment.
CoRR, 2020

Explainable robotic systems: Interpreting outcome-focused actions in a reinforcement learning scenario.
CoRR, 2020

iCub: Learning Emotion Expressions using Human Reward.
CoRR, 2020

Unmanned Aerial Vehicle Control through Domain-Based Automatic Speech Recognition.
Comput., 2020

KutralNet: A Portable Deep Learning Model for Fire Recognition.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Moody Learners - Explaining Competitive Behaviour of Reinforcement Learning Agents.
Proceedings of the Joint IEEE 10th International Conference on Development and Learning and Epigenetic Robotics, 2020

A Comparison of Humanoid Robot Simulators: A Quantitative Approach.
Proceedings of the Joint IEEE 10th International Conference on Development and Learning and Epigenetic Robotics, 2020

A Robust Approach for Continuous Interactive Reinforcement Learning.
Proceedings of the HAI '20: 8th International Conference on Human-Agent Interaction, 2020

2019
Lightweight and efficient octave convolutional neural network for fire recognition.
Proceedings of the IEEE Latin American Conference on Computational Intelligence, 2019

Human feedback in continuous actor-critic reinforcement learning.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

Memory-Based Explainable Reinforcement Learning.
Proceedings of the AI 2019: Advances in Artificial Intelligence, 2019

Reinforcement learning using continuous states and interactive feedback.
Proceedings of the 2nd International Conference on Applications of Intelligent Systems, 2019

2018
Improving interactive reinforcement learning: What makes a good teacher?
Connect. Sci., 2018

Action Selection Methods in a Robotic Reinforcement Learning Scenario.
Proceedings of the IEEE Latin American Conference on Computational Intelligence, 2018

Multi-modal Feedback for Affordance-driven Interactive Reinforcement Learning.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

2017
Teaching Robots With Interactive Reinforcement Learning.
PhD thesis, 2017

Agent-advising approaches in an interactive reinforcement learning scenario.
Proceedings of the 2017 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics, 2017

2016
Training Agents With Interactive Reinforcement Learning and Contextual Affordances.
IEEE Trans. Cogn. Dev. Syst., 2016

Multi-modal integration of dynamic audiovisual patterns for an interactive reinforcement learning scenario.
Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

Learning contextual affordances with an associative neural architecture.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

2015
Interactive reinforcement learning through speech guidance in a domestic scenario.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

2014
Improving reinforcement learning with interactive feedback and affordances.
Proceedings of the 4th International Conference on Development and Learning and on Epigenetic Robotics, 2014

2010
Indirect Training with Error Backpropagation in Gray-Box Neural Model: Application to a Chemical Process.
Proceedings of the SCCC 2010, 2010

2007
Indirect Training of Grey-Box Models: Application to a Bioprocess.
Proceedings of the Advances in Neural Networks, 2007


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