The detailed description of behaviour of the interacting parties is becoming more and more
important in human–robot interaction (HRI), especially in social robotics (SR). With the rise …

This paper introduces novel methods which could improve the efficiency of the automated
knowledge extraction methods used in the FRIQ-learning (Fuzzy Rule Interpolationbased Q …

The aim of the study is to create a performance evaluation controlling model to evaluate the
performance of tourism enterprises as a function of the economic effects of COVID-19. As a …

The learning process of conventional reinforcement learning methods, such as Q-learning
and SARSA typically start with an empty knowledge base. In each iteration step, the initial …

The adaptation of ethologically inspired behaviour models for human-machine interaction
eg in Ethorobotics has become a challenging research topic in recent years. This paper …

Human-Robot Interaction (HRI) evaluation is rapidly gaining more interest as the field of
social robotics advances, but determining the effectiveness of the various HRI models can …

The FIVE (Fuzzy Interpolation in Vague Environment) is a possible method for behavior
based control. Mobile robots can be also controlled by a behavior based controller. In …

The field of the reinforcement learning (RL) is the set of the trial-and-error types machine
learning methods. The learning of the conventional RL algorithms, such as Q-learning …

A Fuzzy Rule Interpolation-based (FRI) fuzzy automaton for controlling a football match
simulation is going to be introduced in this paper. Controlling the agents (football players) of …

One possible way to describe complex behaviours for robots is to use a fuzzy rule based
system. The Fuzzy Behaviour Description Language (FBDL) is a language designed to be …