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Automatic Skill Acquisition in Reinforcement Learning Using Graph Centrality Measures

Related publications (41)

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Character Networks and Centrality

Yannick Rochat

A character network represents relations between characters from a text; the relations are based on text proximity, shared scenes/events, quoted speech, etc. Our project sketches a theoretical framework for character network analysis, bringing together nar ...

University of Lausanne2014

Privacy and Dynamics of Social Networks

Pedram Pedarsani

Over the past decade, investigations in different fields have focused on studying and understanding real networks, ranging from biological to social to technological. These networks, called complex networks, exhibit common topological features, such as a h ...

EPFL2013

Direct Negative Opinions in Online Discussions

Boi Faltings, Claudiu-Cristian Musat, Philippe Henri Jean Roussille

In this paper we investigate the impact of antagonism in online discussions. We define antagonism as a new class of textual opinions - direct sentiment towards the authors of previous comments. We detect the negative sentiment using aspect-based opinion mi ...

2013

Privacy and Dynamics of Social Networks (PhD Thesis: pre-print)

Pedram Pedarsani

2012

Graph-Based Information Processing

Amin Karbasi

We live in a world characterized by massive information transfer and real-time communication. The demand for efficient yet low-complexity algorithms is widespread across different fields, including machine learning, signal processing and communications. Mo ...

EPFL2012

Information Processing and Structure of Dynamical Networks

Ali Ajdari Rad

Networks are everywhere and we are confronted with many networks in our daily life. Networks such as Internet, World Wide Web, social, biological and economical networks have been subject to extensive studies in the last decade. The volume of publications ...

EPFL2011

Estimating small-world topology of neural networks from multi-electrode recordings

Wulfram Gerstner, Joao Emanuel Felipe Gerhard

Since the seminal work of Watts in the late 90s, graph-theoretic analyses have been performed on many complex dynamic networks, including brain structures. Most studies have focused on functional connectivity defined between whole brain regions, using imag ...

2011

Estimation of small-world topology of cortical networks using Generalized Linear Models

Wulfram Gerstner, Joao Emanuel Felipe Gerhard

Since the seminal work of Watts & Strogatz and others in the late 90s [1], graph-theoretic analyses have been performed on many complex dynamic networks, including brain structures. Most studies have focused on functional connectivity defined between whole ...

2011

Automatic skill acquisition in Reinforcement Learning using connection graph stability centrality

Martin Hasler, Ali Ajdari Rad

Reinforcement Learning (RL) is an approach for training agent's behavior through trial-and-error interactions with a dynamic environment. An important problem of RL is that in large domains an enormous number of decisions are to be made. Hence, instead of ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

Synchronizability of dynamical networks: different measures and coincidence

Ali Ajdari Rad, Mahdi Jalili

In this paper, we list four different interpretations of synchronizability, study their profile in different network structures and give evidence that they do not coincide, in general. By changing the network topological properties, their behavior is track ...

2009