Q-Learning Algorithm Module in Hybrid Artificial Neural Network Systems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00217982" target="_blank" >RIV/68407700:21230/14:00217982 - isvavai.cz</a>

Výsledek na webu

<a href="http://link.springer.com/chapter/10.1007/978-3-319-06740-7_11" target="_blank" >http://link.springer.com/chapter/10.1007/978-3-319-06740-7_11</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-06740-7_11" target="_blank" >10.1007/978-3-319-06740-7_11</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Q-Learning Algorithm Module in Hybrid Artificial Neural Network Systems

Popis výsledku v původním jazyce

Presented topic is from the research field called Artificial Life, but contributes also to the field of Artificial Intelligence (AI), Robotics and potentially into many other aspects of research. In this paper, there is reviewed and tested new approach to autonomous design of agent architectures. This novel approach is inspired by inherited modularity of biological brains. During designing of new brains, the evolution is not directly connecting individual neurons. Rather than that, it composes new brains by connecting larger, widely reused areas (modules). In this approach, agent architectures are represented as hybrid artificial neural networks composed of heterogeneous modules. Each module can implement different selected algorithm. Rather than describing this framework, this paper focuses on designing of one module. Such a module represents one component of hybrid neural network and can seamlessly integrate a selected algorithm into the node. The course of design of such a module is

Název v anglickém jazyce

Q-Learning Algorithm Module in Hybrid Artificial Neural Network Systems

Popis výsledku anglicky

Presented topic is from the research field called Artificial Life, but contributes also to the field of Artificial Intelligence (AI), Robotics and potentially into many other aspects of research. In this paper, there is reviewed and tested new approach to autonomous design of agent architectures. This novel approach is inspired by inherited modularity of biological brains. During designing of new brains, the evolution is not directly connecting individual neurons. Rather than that, it composes new brains by connecting larger, widely reused areas (modules). In this approach, agent architectures are represented as hybrid artificial neural networks composed of heterogeneous modules. Each module can implement different selected algorithm. Rather than describing this framework, this paper focuses on designing of one module. Such a module represents one component of hybrid neural network and can seamlessly integrate a selected algorithm into the node. The course of design of such a module is

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Modern Trends and Techniques in Computer Science

ISBN

978-3-319-06739-1

ISSN

2194-5357

e-ISSN

—

Počet stran výsledku

11

Strana od-do

117-127

Název nakladatele

Springer

Místo vydání

Heidelberg

Místo konání akce

on-line

Datum konání akce

28. 4. 2014

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

—