Search Results - subject:"Learning algorithms"

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A note on the representative adaptive learning algorithm

Berardi, Michele; Galimberti, Jaqueson K. - 2014

We compare forecasts from different adaptive learning algorithms and calibrations applied to US real-time data on …

Persistent link: https://www.econbiz.de/10010344932

A note on the representative adaptive learning algorithm

Berardi, Michele; Galimberti, Jaqueson K. - In: Economics letters 124 (2014) 1, pp. 104-107

Persistent link: https://www.econbiz.de/10010490580

Inferring urban land use using large-scale social media check-in data

Zhan, Xianyuan; Ukkusuri, Satish V.; Zhu, Feng - In: Networks and spatial economics : a journal of … 14 (2014) 3/4, pp. 647-667

Persistent link: https://www.econbiz.de/10011308762

Artificial Neural Networks

BARDAªUC, Leila; POPESCU, Andrei - In: Alma Mater University journal 6 (2013) 1, pp. 27-30

You do not have to look far and we can see that every electronic device is built around at least one processor which is a miniature brain, in the most simplified way (borrows a few features that help to control that device). Scientists try to simulate a brain to fully comply with the biological...

Persistent link: https://www.econbiz.de/10011066078

LANGUAGE, CATEGORIZATION, AND CONVENTION

NARENS, LOUIS; JAMESON, KIMBERLY A.; KOMAROVA, NATALIA L.; … - In: Advances in Complex Systems (ACS) 15 (2012) 03, pp. 1150022-1

Linguistic meaning is a convention. This article investigates how such conventions can arise for color categories in populations of simulated "agents". The method uses concepts from evolutionary game theory: A language game where agents assign names to color patches and is played repeatedly by...

Persistent link: https://www.econbiz.de/10010550848

Empirical evaluation methods for multiobjective reinforcement learning algorithms

Vamplew, Peter; Dazeley, Richard; Berry, Adam; … - 2011

studies. Two classes of multiobjective reinforcement learning algorithms are identified, and appropriate evaluation metrics … are demonstrated via an empirical comparison of two example learning algorithms. ?? 2010 The Author(s). …

Persistent link: https://www.econbiz.de/10009484645

Financial Time Series and Neural Networks in a Minority Game Context

Grilli, Luca; Sfrecola, Angelo; Russo, Massimo Alfonso - Dipartimento di Scienze Economiche, Matematiche e … - 2010

In this paper we consider financial time series from U.S. Fixed Income Market, S&P500, DJ Eurostoxx 50, Dow Jones,Mibtel and Nikkei 225. It is well known that financial time series reveal some anomalies regarding the EfficientMarketHypothesis and some scaling behaviour, such as fat tails and...

Persistent link: https://www.econbiz.de/10008455826

A Neural Networks approach to Minority Game

Grilli, Luca; Sfrecola, Angelo - Dipartimento di Scienze Economiche, Matematiche e … - 2009

history for making their decisions, we propose a neural networks approach with learning algorithms in order to determine …

Persistent link: https://www.econbiz.de/10008455823

A Neural Networks approach to Minority Game

Grilli, Luca; Sfrecola, Angelo - Dipartimento di Scienze Economiche, Matematiche e … - 2005

history for making their decisions, we propose a neural networks approach with learning algorithms in order to determine …

Persistent link: https://www.econbiz.de/10005434756

Neural Networks to Predict Financial Time Series in a Minority Game Context

Grilli, Luca; Sfrecola, Angelo - Dipartimento di Scienze Economiche, Matematiche e … - 2005

In this paper we consider financial time series from U.S. Fixed Income Market, S&P500, Exchange Market and Oil Market. It is well known that financial time series reveal some anomalies as regards the Efficient Market Hypotesis and some scaling behavior is evident such as fat tails and clustered...

Persistent link: https://www.econbiz.de/10005628770