David Vincze

Chuo University · Department of Precision Mechanics

Reinforcement Learning (RL) methods became popular decades ago and still maintain to be one of the mainstream topics in computational intelligence. Countless different RL methods and variants can be found in the literature, each one having its own advantages and disadvantages in a specific application domain. Representation of the revealed knowledg...

The concept of ‘Future Internet’, ‘Internet of Things’ and ‘3D Internet’ opens a novel way for modeling ethological test s by rebuilding models of human - animal interaction in an augmented environment as an interactive mixture of virtual actors and real human observers. On the one hand these experiments can serve as a proof of concept, as a kind o...

This paper presents human-robot interaction interfaces based on ethological studies. An ethological test procedure was modeled with the application of a fuzzy rule interpolation based fuzzy automaton. This fuzzy automaton was loaded with rules formed from the extracted ethological knowledge. Using the behaviours supplied by the fuzzy automaton as c...

A novel aspect of human-robot interaction (HRI) can be put on the basis, that the robot side is implemented on a state-machine (fuzzy automaton), which reacts the human intervention as a function of the robot state and the human action. This platform is suitable for implementing quite complicated action-reaction sequences, like the interaction of h...

Fuzzy Rule Interpolation (FRI) methods are efficient structures for knowledge-representation with relatively few rules. In spite of their good knowledge representation efficiency, their high computational demand makes the FRI methods hardly suitable for embedded real-time applications, for which short reasoning time has a high importance. On the ot...

Source code and docs: https://github.com/szaguldo-kamaz/wysiwyg-iloc -------------------------------------------------------------------------------------------------------------------------------------- Indoor localization methods provide pose information in their own virtual coordinate systems. Adjusting these custom virtual spaces to the real p...

Jelen cikk egy fuzzy automatával vezérelt futball szimuláció modelljét mutatja be. A szimuláció ágenseinek (játékosainak) irányítása olyan fuzzy szabálybázisokkal történik, amelyekben csak a tényleges működéshez szükséges, leglényegesebbnek vélt szabályok lettek definiálva. Az ilyen, ritka fuzzy szabálybázisokat a klasszikus fuzzy következtető rend...

This paper introduces a way to control the Pong game automatically with the usage of FRIQ-learning (Fuzzy Rule Interpolation-based Q-learning). The FRIQ-learning method can be a solution to such a problem which has a small state-space. The system starts with an empty knowledge base and the system constructs the final rule-base during the simulation...

The Fuzzy Rule Interpolation (FRI)-based Fuzzy Automaton is an efficient structure for describing complex behaviour models in a relatively simple manner. The goal of this paper is to introduce a novel declarative behaviour description language which is created for supporting special needs of ethologically inspired behaviour model definition. For th...

The Virtual Collaboration Arena (VirCA) is a modular, easy to use 3D framework supporting the development of augmented (real and virtual) reality applications. To apply the services provided by VirCA, special VirCA interfaces are needed in the actual programming environment. Native interface does not exist for some special environments, like e.g. f...

For implementing ethologically inspired robot behavior in this paper a platform based on fuzzy automaton (fuzzy state-machine) is suggested. It can react the human intervention as a function of the robot state and the human action. This platform is suitable for implementing quite complicated action-reaction sequences, like the interaction of human...

This paper presents a concrete implementation of the Fuzzy Rule Interpolation (FRI) method called `FIVE'. FIVE is an acronym for Fuzzy rule Interpolation based on Vague Environment. The method itself tends to be a fast and simple to use application oriented FRI technique. Therefore the main goal of this paper to study the speed performance issues o...

Reinforcement Learning (RL) is a widely known topic in computational intelligence. In the RL concept the problem needed to be solved is hidden in the feedback of the environment, called rewards. Using these rewards the system can learn which action is considered to be the best choice in a given state. One of the most frequently used RL method is th...

One way of handling Human-Robot Interaction (HRI) is based on the concept, that the robot acts like an animal companion to human. According to this paradigm the Robot should not be molded to mimic the human being, and form human-to-human like communication, but to follow the existing biological examples and form inter-species interaction. The 20.00...

One way of handling Human-Robot Interaction (HRI) is based on the concept, that the robot acts like an animal companion to human. According to this paradigm the Robot should not be molded to mimic the human being, and form human-to-human like communication, but to follow the existing biological examples and form inter-species interaction. The 20.00...

Reinforcement learning is a well known topic in computational intelligence. It can be used to solve control problems in unknown environments without defining an exact method on how to solve problems in various situations. Instead the goal is defined and all the actions done in the different states are given feedback, called reward or punishment (po...

Fuzzy Q-learning, the fuzzy extension of the Reinforcement Learning (RL) is a well known topic in computational intelligence. It can be used to tackle control problems in unknown continuous environments without defining an exact method on how to solve it explicitly. In the RL concept the problem needed to be solved is hidden in the feedback of the...

Relatively few Fuzzy Rule Interpolation (FRI) techniques can be found among the practical fuzzy rule based applications. Many of them have limitations from the direct application point of view, for example they can be applied only in one dimensional case, or defined based on the two closest surrounding rules of the actual observation. Additionally...

Several Fuzzy Rule Interpolation (FRI) techniques have limitations from the direct application point of view, for example their applicability is limited to the one dimensional case, or they can be defined only based on the two closest surrounding rules of the actual observation. This is the reason why relatively few FRI methods can be found among t...

From the viewpoint of Behaviour based Control many control tasks can be divided into separate behaviour components. By defining the relevant behaviour components, the actual control action can be constructed based on the individual control actions of the component behaviours. In this case the control action is either related to an individual behavi...