Francisco Cruz | DeepAI

DeepAI AI Chat

Featured Co-authors

Stefan Wermter
125 publications
Matthew E. Taylor
39 publications
Alessandra Sciutti
35 publications
Pablo Barros
33 publications
Sven Magg
21 publications
Richard Dazeley
20 publications
Cleber Zanchettin
19 publications
German I. Parisi
18 publications
Sunil Aryal
17 publications
Nikhil Churamani
17 publications
David Macêdo
17 publications

∙ 08/25/2023

Asch Meets HRI: Human Conformity to Robot Groups

We present a research outline that aims at investigating group dynamics ...

0 Jasmin Bernotat, et al. ∙

∙ 12/14/2022

Explaining Agent's Decision-making in a Hierarchical Reinforcement Learning Scenario

Reinforcement learning is a machine learning approach based on behaviora...

0 Hugo Muñoz, et al. ∙

∙ 12/06/2022

Reinforcement Learning for UAV control with Policy and Reward Shaping

In recent years, unmanned aerial vehicle (UAV) related technology has ex...

0 Cristian Millán-Arias, et al. ∙

∙ 11/23/2022

Introspection-based Explainable Reinforcement Learning in Episodic and Non-episodic Scenarios

With the increasing presence of robotic systems and human-robot environm...

0 Niclas Schroeter, et al. ∙

∙ 10/11/2022

Broad-persistent Advice for Interactive Reinforcement Learning Scenarios

The use of interactive advice in reinforcement learning scenarios allows...

0 Francisco Cruz, et al. ∙

∙ 10/07/2022

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

Deep Q-Networks algorithm (DQN) was the first reinforcement learning alg...

0 Adrian Ly, et al. ∙

∙ 09/15/2022

Intuitive Robot Programming by Capturing Human Manufacturing Skills: A Framework for the Process of Glass Adhesive Application

There is a great demand for the robotization of manufacturing processes ...

0 Mihail Babcinschi, et al. ∙

∙ 07/07/2022

Evaluating Human-like Explanations for Robot Actions in Reinforcement Learning Scenarios

Explainable artificial intelligence is a research field that tries to pr...

0 Francisco Cruz, et al. ∙

∙ 10/15/2021

A Broad-persistent Advising Approach for Deep Interactive Reinforcement Learning in Robotic Environments

Deep Reinforcement Learning (DeepRL) methods have been widely used in ro...

0 Hung Son Nguyen, et al. ∙

∙ 08/20/2021

Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework and Survey

Broad Explainable Artificial Intelligence moves away from interpreting i...

0 Richard Dazeley, et al. ∙

∙ 08/18/2021

Explainable Deep Reinforcement Learning Using Introspection in a Non-episodic Task

Explainable reinforcement learning allows artificial agents to explain t...

0 Angel Ayala, et al. ∙

∙ 08/08/2021

Learning Proxemic Behavior Using Reinforcement Learning with Cognitive Agents

Proxemics is a branch of non-verbal communication concerned with studyin...

0 Cristian Millán-Arias, et al. ∙

∙ 07/07/2021

Levels of explainable artificial intelligence for human-aligned conversational explanations

Over the last few years there has been rapid research growth into eXplai...

10 Richard Dazeley, et al. ∙

∙ 02/04/2021

Persistent Rule-based Interactive Reinforcement Learning

Interactive reinforcement learning has allowed speeding up the learning ...

0 Adam Bignold, et al. ∙

∙ 09/21/2020

Human Engagement Providing Evaluative and Informative Advice for Interactive Reinforcement Learning

Reinforcement learning is an approach used by intelligent agents to auto...

0 Adam Bignold, et al. ∙

∙ 09/09/2020

Unmanned Aerial Vehicle Control Through Domain-based Automatic Speech Recognition

Currently, unmanned aerial vehicles, such as drones, are becoming a part...

4 Ruben Contreras, et al. ∙

∙ 08/16/2020

KutralNet: A Portable Deep Learning Model for Fire Recognition

Most of the automatic fire alarm systems detect the fire presence throug...

0 Angel Ayala, et al. ∙

∙ 08/11/2020

A Comparison of Humanoid Robot Simulators: A Quantitative Approach

Research on humanoid robotic systems involves a considerable amount of c...

0 Angel Ayala, et al. ∙

∙ 07/30/2020

Moody Learners – Explaining Competitive Behaviour of Reinforcement Learning Agents

Designing the decision-making processes of artificial agents that are in...

0 Pablo Barros, et al. ∙

∙ 07/07/2020

Deep Reinforcement Learning with Interactive Feedback in a Human-Robot Environment

Robots are extending their presence in domestic environments every day, ...

0 Ithan Moreira, et al. ∙

∙ 07/03/2020

A Conceptual Framework for Externally-influenced Agents: An Assisted Reinforcement Learning Review

A long-term goal of reinforcement learning agents is to be able to perfo...

0 Adam Bignold, et al. ∙

∙ 06/24/2020

Explainable robotic systems: Interpreting outcome-focused actions in a reinforcement learning scenario

Robotic systems are more present in our society every day. In human-robo...

0 Francisco Cruz, et al. ∙

∙ 03/30/2020

iCub: Learning Emotion Expressions using Human Reward

The purpose of the present study is to learn emotion expression represen...

0 Nikhil Churamani, et al. ∙

∙ 04/15/2019

Improving interactive reinforcement learning: What makes a good teacher?

Interactive reinforcement learning has become an important apprenticeshi...

4 Francisco Cruz, et al. ∙

∙ 07/26/2018

Multi-modal Feedback for Affordance-driven Interactive Reinforcement Learning

Interactive reinforcement learning (IRL) extends traditional reinforceme...

0 Francisco Cruz, et al. ∙

∙ 05/07/2018

A probabilistic framework for handwritten text line segmentation

We successfully combine Expectation-Maximization algorithm and variation...

0 Francisco Cruz, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world