WorldCat Identities

Hutter, Marcus

Overview
Works: 15 works in 86 publications in 2 languages and 2,213 library holdings
Genres: Conference papers and proceedings 
Roles: Author, Editor, Creator
Classifications: Q335, 006.31
Publication Timeline
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Most widely held works by Marcus Hutter
Universal artificial intelligence : sequential decisions based on algorithmic probability by Marcus Hutter( Book )

22 editions published between 2005 and 2010 in English and German and held by 246 WorldCat member libraries worldwide

This volume presents sequential decision theory from a novel algorithmic information theory perspective. Considered problem classes include sequence prediction, strategic games, function minimization, reinforcement and supervised learning
Algorithmic learning theory : 18th international conference, ALT 2007, Sendai, Japan, October 1-4, 2007 : proceedings by Marcus Hutter( Book )

23 editions published between 2007 and 2010 in English and held by 133 WorldCat member libraries worldwide

Annotation
Algorithmic Learning Theory 21st International Conference, ALT 2010, Canberra, Australia, October 6-8, 2010. Proceedings by Marcus Hutter( )

11 editions published between 2007 and 2010 in English and held by 65 WorldCat member libraries worldwide

Annotation
Recent advances in reinforcement learning : 9th European Workshop, EWRL 2011, Athens, Greece, September 9-11, 2011 : revised selected papers by Scott Sanner( Book )

9 editions published in 2012 in English and held by 26 WorldCat member libraries worldwide

This book constitutes revised and selected papers of the 9th European Workshop on Reinforcement Learning, EWRL 2011, which took place in Athens, Greece in September 2011. The papers presented were carefully reviewed and selected from 40 submissions. The papers are organized in topical sections online reinforcement learning, learning and exploring MDPs, function approximation methods for reinforcement learning, macro-actions in reinforcement learning, policy search and bounds, multi-task and transfer reinforcement learning, multi-agent reinforcement learning, apprenticeship and inverse reinforcement learning and real-world reinforcement learning
Instantonen in der QCD : Theorie und Anwendungen des Instanton-Flüssigkeit-Modells by Marcus Hutter( )

5 editions published between 1995 and 1996 in German and held by 18 WorldCat member libraries worldwide

Sequence prediction for non-stationary processes( )

1 edition published in 2006 in English and held by 15 WorldCat member libraries worldwide

Learning in reactive environments with arbitrary dependence( )

1 edition published in 2006 in English and held by 15 WorldCat member libraries worldwide

Kolmogorov complexity and applications 06051 abstracts collection ; Dagstuhl seminar( )

1 edition published in 2006 in English and held by 15 WorldCat member libraries worldwide

Complexity monotone in conditions and future prediction errors( )

1 edition published in 2006 in English and held by 15 WorldCat member libraries worldwide

Artificial general intelligence : proceedings of the third conference on artificial general intelligence, AGI 2010, Lugano, Switzerland by Conference on Artificial General Intelligence( Book )

4 editions published in 2010 in English and held by 9 WorldCat member libraries worldwide

Recent advances in reinforcement learning 9th european workshop, EWRL 2011, Athens, Greece, September 9 - 11, 2011 ; revised selected papers( )

1 edition published in 2012 in English and held by 2 WorldCat member libraries worldwide

Annotation
Image based automatic vehicle damage detection by Srimal Jayawardena( )

1 edition published in 2013 in English and held by 1 WorldCat member library worldwide

Automatically detecting vehicle damage using photographs taken at the accident scene is very useful as it can greatly reduce the cost of processing insurance claims, as well as provide greater convenience for vehicle users. An ideal scenario would be where the vehicle user can upload a few photographs of the damaged car taken from a mobile phone and have the damage assessment and insurance claim processing done automatically. However, such a solution remains a challenging task due to a number of factors. For a start, the scene of the accident is typically an unknown and uncontrolled outdoor environment with a plethora of factors beyond our control including scene illumination and the presence of surrounding objects which are not known a priori. In addition, since vehicles have very reflective metallic bodies the photographs taken in such an uncontrolled can be expected to have a considerable amount of inter object reflection. Therefore, the application of standard computer vision techniques in this context is a very challenging task. Moreover, solving this task opens up a fascinating repertoire of computer vision problems which need to be addressed in the context of a very challenging scenario. This thesis describes research undertaken to address the problem of automatic vehicle damage detection using photographs. A pipeline adressing a vertical slice of the broad problem is considered while focusing on mild vehicle damage detection. We propose to use 3D CAD models of undamaged vehicles which are used to obtain ground truth information in order to infer what the vehicle with mild damage in the photograph should have looked like, if it had not been damaged. To this, end we develop 3D pose estimation algorithms to register an undamaged 3D CAD model over a photograph of the known damaged vehicle. We present a 3D pose estimation method using image gradient information of the photograph and the 3D model projection. We show how the 3D model projection at the recovered 3D pose can be used to identify components of a vehicle in the photograph which may have mild damage. In addition, we present a more robust 3D pose estimation method by minimizing a novel illumination invariant distance measure, which is based on a Mahalanobis distance between attributes of the 3D model projection and the pixels in the photograph. In principle, image edges which are not present in the 3D CAD model projection can be considered to be vehicle damage. However, since the vehicle body is very reflective, there is a large amount of inter object reflection in the photograph which may be misclassified as damage. In order to detect image edges caused by inter object reflection, we propose to apply multi-view geometry techniques on two photographs of the vehicle taken from different viewpoints. To this end, we also develop a robust method to obtain reliable point correspondences across the photographs which are dominated by large reflective and mostly homogeneous regions. The performance of the proposed methods are experimentally evaluated on real photographs using 3D CAD models
Optimal sequential decisions based on algorithmic probability by Marcus Hutter( Book )

1 edition published in 2006 in English and held by 1 WorldCat member library worldwide

Algorithmic Learning Theory 14th International Conference, ALT 2003, Sapporo, Japan, October 17-19, 2003. Proceedings by Ricard Gavaldá( )

2 editions published in 2007 in English and held by 1 WorldCat member library worldwide

 
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Universal artificial intelligence : sequential decisions based on algorithmic probability
Alternative Names
Hutter, M.

Marcus Hutter Computer scientist

Marcus Hutter deutscher Informatiker und Professor an der Australian National University

Marcus Hutter informaticus uit Australië

マーカス・ハッター

馬庫斯·胡特

Languages
English (80)

German (6)

Covers
Algorithmic learning theory : 18th international conference, ALT 2007, Sendai, Japan, October 1-4, 2007 : proceedingsAlgorithmic Learning Theory 21st International Conference, ALT 2010, Canberra, Australia, October 6-8, 2010. Proceedings