Technical Reports - Query Results
Your query term was 'number = 2012'17 reports found
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- OFAI-TR-2012-17 (
281kB PDF file)The Relation of Hubs to the Doddington Zoo in Speaker Verification
- Dominik Schnitzer, Arthur Flexer, Jan Schlueter
- In speaker verification systems there exists the well-known
phenomenon of speakers which are very problematic to verify
and have been given various metaphoric animal names.
Our work connects this so-called 'Doddington zoo' and the
animals of the whole 'biometric menagerie' to the problem of
'hubs' in high dimensional data spaces, which was recently
the topic of a number of publications in the machine learning
literature. Due to a general problem of measuring distances in
high dimensional data spaces, hub objects emerge which have
a high similarity to a large number of data items. This is a
novel aspect of the 'curse of dimensionality' which adversely
affects classification and identification performance. In a series
of experiments we try to understand the 'Doddington zoo'
problem with respect to the notions of hubs and anti-hubs.
Keywords: Speaker Verification, Hubs, Normalization, Machine Learning
- In speaker verification systems there exists the well-known
phenomenon of speakers which are very problematic to verify
and have been given various metaphoric animal names.
Our work connects this so-called 'Doddington zoo' and the
animals of the whole 'biometric menagerie' to the problem of
'hubs' in high dimensional data spaces, which was recently
the topic of a number of publications in the machine learning
literature. Due to a general problem of measuring distances in
high dimensional data spaces, hub objects emerge which have
a high similarity to a large number of data items. This is a
novel aspect of the 'curse of dimensionality' which adversely
affects classification and identification performance. In a series
of experiments we try to understand the 'Doddington zoo'
problem with respect to the notions of hubs and anti-hubs.
- OFAI-TR-2012-16 ( 1946kB PDF file)
Structure and stability of online chat networks built on emotion-carrying links
- Vladimir Gligorijevic, Marcin Skowron, Bosiljka Tadic
- High-resolution data of online chats are studied as a physical system in the laboratory in order to quantify collective behavior of users. Our analysis reveals strong regularities characteristic of natural systems with additional features. In particular, we find self-organized dynamics with long-range correlations in user actions and persistent associations among users that have the properties of a social network. Furthermore, the evolution of the graph and its architecture with specific k-core structure are shown to be related with the type and the emotion arousal of exchanged messages. Partitioning of the graph by deletion of the links which carry high arousal messages exhibits critical fluctuations at the percolation threshold.
Keywords: Publications List Interact, Social structure emerges in online chats, Users associate by emotion-carrying messages, Physics and computer science reveal new dimension of user behaviors
- High-resolution data of online chats are studied as a physical system in the laboratory in order to quantify collective behavior of users. Our analysis reveals strong regularities characteristic of natural systems with additional features. In particular, we find self-organized dynamics with long-range correlations in user actions and persistent associations among users that have the properties of a social network. Furthermore, the evolution of the graph and its architecture with specific k-core structure are shown to be related with the type and the emotion arousal of exchanged messages. Partitioning of the graph by deletion of the links which carry high arousal messages exhibits critical fluctuations at the percolation threshold.
- OFAI-TR-2012-15 ( 380kB PDF file)
Local and Global Scaling Reduce Hubs in Space
- Dominik Schnitzer, Arthur Flexer, Markus Schedl, Gerhard Widmer
- "Hubness" has recently been identified as a general problem of high dimensional data spaces, manifesting
itself in the emergence of objects, so-called hubs, which tend to be among the k nearest
neighbors of a large number of data items. As a consequence many nearest neighbor relations
in the distance space are asymmetric, that is, object y is amongst the nearest neighbors of x but
not vice versa. The work presented here discusses two classes of methods that try to symmetrize
nearest neighbor relations and investigates to what extent they can mitigate the negative effects of
hubs. We evaluate local distance scaling and propose a global variant which has the advantage of
being easy to approximate for large datasets and of having a probabilistic interpretation. Both local
and global approaches are shown to be effective especially for high-dimensional datasets, which
are affected by high hubness. Both methods lead to a strong decrease of hubness in these datasets,
while at the same time improving properties like classification accuracy. We evaluate the methods
on a large number of public machine learning datasets and synthetic data. Finally we present a real-world application where we are able to achieve significantly higher retrieval quality.
Keywords: local and global scaling, shared near neighbors, hubness, classification, curse of dimensionality, nearest neighbor relation
- "Hubness" has recently been identified as a general problem of high dimensional data spaces, manifesting
itself in the emergence of objects, so-called hubs, which tend to be among the k nearest
neighbors of a large number of data items. As a consequence many nearest neighbor relations
in the distance space are asymmetric, that is, object y is amongst the nearest neighbors of x but
not vice versa. The work presented here discusses two classes of methods that try to symmetrize
nearest neighbor relations and investigates to what extent they can mitigate the negative effects of
hubs. We evaluate local distance scaling and propose a global variant which has the advantage of
being easy to approximate for large datasets and of having a probabilistic interpretation. Both local
and global approaches are shown to be effective especially for high-dimensional datasets, which
are affected by high hubness. Both methods lead to a strong decrease of hubness in these datasets,
while at the same time improving properties like classification accuracy. We evaluate the methods
on a large number of public machine learning datasets and synthetic data. Finally we present a real-world application where we are able to achieve significantly higher retrieval quality.
- OFAI-TR-2012-14 ( 14136kB PDF file)
Evolving Topology on the Network of Online Chats
- Vladimir Gligorijevic, Marcin Skowron, Bosiljka Tadic
- Large amount of data collected at Web portals contain valuable information to study human behavior in the on-line communications. Recently a powerful methodology was developed to study the emergence of the collective emotional behaviors of Blog users, by combining the methods of statistical physics of complex systems with the machine-learning techniques for text analysis.
Mapping the high-resolution data onto a suitable network structure makes a starting point in this approach, on which the quantitative analysis within the graph theory is based. In this work we use network mapping approach to analyse the users collective behaviors in the online chats. Specifically, having in mind character of the dynamics in IRC channels, here we analyse the evolution of
the network that emerges via user contacts and in particular, evolving specific topology features on such network over successive time windows.
Keywords: Publications List Interact, Social and Information Networks, Data Analysis, Text Analysis, Online Communication Affective Computing
- Large amount of data collected at Web portals contain valuable information to study human behavior in the on-line communications. Recently a powerful methodology was developed to study the emergence of the collective emotional behaviors of Blog users, by combining the methods of statistical physics of complex systems with the machine-learning techniques for text analysis.
Mapping the high-resolution data onto a suitable network structure makes a starting point in this approach, on which the quantitative analysis within the graph theory is based. In this work we use network mapping approach to analyse the users collective behaviors in the online chats. Specifically, having in mind character of the dynamics in IRC channels, here we analyse the evolution of
the network that emerges via user contacts and in particular, evolving specific topology features on such network over successive time windows.
- OFAI-TR-2012-13 ( 377kB PDF file)
Affect Listeners - From dyads to group interactions with affective dialog systems
- Marcin Skowron, Stefan Rank
- Affect Listeners are applied as tools for studying the role
of emotions in online communication. They need to interact both in
dyads as well as in group settings with multiple users. In this paper,
we present the evolution of such affective dialog systems from
a focus on dyadic interaction to multi-party interaction on chat networks.
Starting from experiments on the use of these dialog systems
in virtual dyadic settings, we outline the requirements, design and
implementation decisions necessary to apply the systems to affective
interactions with multiple users. Finally, we introduce two realisations
of Interactive Affective Bots designed for such interaction scenarios
that integrate modelling of individuals and groups as part of
their decision mechanism.
Keywords: Publications List Interact, affective dialog system, affective human-computer interactions, agent control architecture
- Affect Listeners are applied as tools for studying the role
of emotions in online communication. They need to interact both in
dyads as well as in group settings with multiple users. In this paper,
we present the evolution of such affective dialog systems from
a focus on dyadic interaction to multi-party interaction on chat networks.
Starting from experiments on the use of these dialog systems
in virtual dyadic settings, we outline the requirements, design and
implementation decisions necessary to apply the systems to affective
interactions with multiple users. Finally, we introduce two realisations
of Interactive Affective Bots designed for such interaction scenarios
that integrate modelling of individuals and groups as part of
their decision mechanism.
- OFAI-TR-2012-12 ( 1110kB PDF file)
Entropy-growth-based model of emotionally charged online dialogues
- Julian Sienkiewicz, Marcin Skowron, Georgios Paltoglou, Janusz Holyst
- We analyze emotionally annotated massive data from IRC (Internet Relay Chat) and model the dialogues between its participants by assuming that the driving force for the discussion is the entropy growth of emotional probability distribution. This process is claimed to be correlated to the emergence of the power-law distribution of the discussion lengths observed in the dialogues. We perform numerical simulations based on the noticed phenomenon obtaining a good agreement with the real data. Finally, we propose a method to artificially prolong the duration of the discussion that relies on the entropy of emotional probability distribution.
Keywords: Publications List Interact, Computation and Language, Social and Information Networks, Data Analysis, Statistics and Probability, Physics and Society
- We analyze emotionally annotated massive data from IRC (Internet Relay Chat) and model the dialogues between its participants by assuming that the driving force for the discussion is the entropy growth of emotional probability distribution. This process is claimed to be correlated to the emergence of the power-law distribution of the discussion lengths observed in the dialogues. We perform numerical simulations based on the noticed phenomenon obtaining a good agreement with the real data. Finally, we propose a method to artificially prolong the duration of the discussion that relies on the entropy of emotional probability distribution.
- OFAI-TR-2012-11 ( 762kB PDF file)
Unsupervised Feature Learning for Speech and Music Detection in Radio Broadcasts
- Jan Schlueter, Reinhard Sonnleitner
- Detecting speech and music is an elementary step in extracting information
from radio broadcasts. Existing solutions either rely on
general-purpose audio features, or build on features specifically
engineered for the task. Interpreting spectrograms as images, we
can apply unsupervised feature learning methods from computer
vision instead. In this work, we show that features learned by a
mean-covariance Restricted Boltzmann Machine partly resemble
engineered features, but outperform three hand-crafted feature sets
in speech and music detection on a large corpus of radio recordings.
Our results demonstrate that unsupervised learning is a powerful
alternative to knowledge engineering.
Keywords: Music Information Retrieval,
- Detecting speech and music is an elementary step in extracting information
from radio broadcasts. Existing solutions either rely on
general-purpose audio features, or build on features specifically
engineered for the task. Interpreting spectrograms as images, we
can apply unsupervised feature learning methods from computer
vision instead. In this work, we show that features learned by a
mean-covariance Restricted Boltzmann Machine partly resemble
engineered features, but outperform three hand-crafted feature sets
in speech and music detection on a large corpus of radio recordings.
Our results demonstrate that unsupervised learning is a powerful
alternative to knowledge engineering.
- OFAI-TR-2012-10 ( 190kB PDF file)
Putting the User in the Center of Music Information Retrieval
- Markus Schedl, Arthur Flexer
- Personalized and context-aware music retrieval and recommendation
algorithms ideally provide music that perfectly
fits the individual listener in each imaginable situation and
for each of her information or entertainment need. Although
first steps towards such systems have recently been
presented at ISMIR and similar venues, this vision is still
far away from being a reality. In this paper, we investigate
and discuss literature on the topic of user-centric music
retrieval and reflect on why the breakthrough in this
field has not been achieved yet. Given the different expertises
of the authors, we shed light on why this topic is a
particularly challenging one, taking a psychological and a
computer science view. Whereas the psychological point
of view is mainly concerned with proper experimental design,
the computer science aspect centers on modeling and
machine learning problems. We further present our ideas
on aspects vital to consider when elaborating user-aware
music retrieval systems, and we also describe promising
evaluation methodologies, since accurately evaluating personalized
systems is a notably challenging task.
Keywords: Music Information Retrieval, Evaluation, User studies
- Personalized and context-aware music retrieval and recommendation
algorithms ideally provide music that perfectly
fits the individual listener in each imaginable situation and
for each of her information or entertainment need. Although
first steps towards such systems have recently been
presented at ISMIR and similar venues, this vision is still
far away from being a reality. In this paper, we investigate
and discuss literature on the topic of user-centric music
retrieval and reflect on why the breakthrough in this
field has not been achieved yet. Given the different expertises
of the authors, we shed light on why this topic is a
particularly challenging one, taking a psychological and a
computer science view. Whereas the psychological point
of view is mainly concerned with proper experimental design,
the computer science aspect centers on modeling and
machine learning problems. We further present our ideas
on aspects vital to consider when elaborating user-aware
music retrieval systems, and we also describe promising
evaluation methodologies, since accurately evaluating personalized
systems is a notably challenging task.
- OFAI-TR-2012-09
Interactive Entertainment of Elder Persons using Intelligent and Emotional Software Agents
- Lisa Szugfil, Robert Trappl
- This project tried to broaden the scope of classical digital
games for elderly people by developing a game which takes social and
emotional aspects into account, gives elderly people the possibility to
bring their own experience into the game and puts cognitive training into
context. A modified version of the classical memory game was
developed, in which a human played against an emotional software
agent. An experiment with eighteen participants (Mage = 84.33 years)
examined the influence of the game-type on the perception of and the
interaction with the software agent. Furthermore the perception of the
playing speed of the counter player was investigated. The results
showed significantly more comments towards the software agent when
playing a personalized memory game, than when playing the classical
memory game. In addition, the mirrored game speed of the software
agent was evaluated as being faster than the human player's own
playing speed but also as optimal by the participants.
Keywords: digital game, elderly people, cognitive training in context, memory, software agent, emotions, playing speed, table top
- This project tried to broaden the scope of classical digital
games for elderly people by developing a game which takes social and
emotional aspects into account, gives elderly people the possibility to
bring their own experience into the game and puts cognitive training into
context. A modified version of the classical memory game was
developed, in which a human played against an emotional software
agent. An experiment with eighteen participants (Mage = 84.33 years)
examined the influence of the game-type on the perception of and the
interaction with the software agent. Furthermore the perception of the
playing speed of the counter player was investigated. The results
showed significantly more comments towards the software agent when
playing a personalized memory game, than when playing the classical
memory game. In addition, the mirrored game speed of the software
agent was evaluated as being faster than the human player's own
playing speed but also as optimal by the participants.
- OFAI-TR-2012-08 ( 1056kB PDF file)
The Hippocampal-Entorhinal Complex performs Bayesian Localization and Error Correction
- T Madl, S Franklin, K Chen, D Montaldi, R Trappl
- The mammalian brain updates representations of spatial location with self-motion cues, a process referred to as path integration. Since self-motion information is inherently inexact and subject to neuronal noise, this process leads to errors, which would accumulate over time if not corrected by sensory information about the environment. In this paper, we propose that the hippocampal-entorhinal complex, the major neuronal correlate representing spatial information, corrects such errors by integrating self-motion information and sensory information about the environment in a Bayes-optimal manner. Based on theoretical arguments as well as empirical data, we propose that hippocampal place cells are able to encode probability distributions and uncertainties of allocentric spatial location, and to use them for Bayesian inference to improve the accuracy of the location representation using different sources of information. We hypothesize about possible neuronal correlates of the components and processes required for such inference. Unlike most previously suggested error correction and spatial cue integration mechanisms, we not only provide a plausible neuronal basis for these mechanisms but also generate concrete predictions from our hypotheses and substantiate them with empirical data. We describe a computational model performing Bayesian localization in arbitrary two-dimensional environments in a biologically plausible way, and use it to replicate neuronal recording data as well as behaviour data in published studies in order to strengthen our claims. Our ideas tie in with a growing body of research suggesting that the brain might behave like a Bayesian machine (the Bayesian brain hypothesis [1]), and provides empirical evidence suggesting that it might employ Bayesian processes on the level of neuronal implementation.
- OFAI-TR-2012-07 ( 290kB PDF file)
Persistent Empirical Wiener Estimation With Adaptive Threshold Selection For Audio Denoising
- Kai Siedenburg
- Exploiting the persistence properties of signals leads
to significant improvements in audio denoising. This
contribution derives a novel denoising operator based
on neighborhood smoothed, Wiener filter like shrinkage.
Relations to the sparse denoising approach via
thresholding are drawn. Further, a rationale for adapting
the threshold level to a performance criterion is
developed. Using a simple but efficient estimator of
the noise level, the introduced operators with adaptive
thresholds are demonstrated to act as attractive alternatives
to the state of the art in audio denoising.
Keywords: Audio denoising
- Exploiting the persistence properties of signals leads
to significant improvements in audio denoising. This
contribution derives a novel denoising operator based
on neighborhood smoothed, Wiener filter like shrinkage.
Relations to the sparse denoising approach via
thresholding are drawn. Further, a rationale for adapting
the threshold level to a performance criterion is
developed. Using a simple but efficient estimator of
the noise level, the introduced operators with adaptive
thresholds are demonstrated to act as attractive alternatives
to the state of the art in audio denoising.
- OFAI-TR-2012-06 ( 139kB PDF file)
A MIREX meta-analysis of hubness in audio music similarity
- Arthur Flexer, Dominik Schnitzer, Jan Schlueter
- We use results from the 2011 MIREX ``Audio Music Similarity and
Retrieval'' task for a meta analysis of the hub phenomenon. Hub songs
appear similar to an undesirably high number of other songs due to a
problem of measuring distances in high dimensional spaces. Comparing
17 algorithms we are able to confirm that different algorithms produce
very different degrees of hubness. We also show that hub songs exhibit
less perceptual similarity to the songs they are close to, according
to an audio similarity function, than non-hub songs. Application of
the recently introduced method of ``mutual proximity'' is able to
decisively improve this situation.
Keywords: Music Information Retrieval, Hubs
- We use results from the 2011 MIREX ``Audio Music Similarity and
Retrieval'' task for a meta analysis of the hub phenomenon. Hub songs
appear similar to an undesirably high number of other songs due to a
problem of measuring distances in high dimensional spaces. Comparing
17 algorithms we are able to confirm that different algorithms produce
very different degrees of hubness. We also show that hub songs exhibit
less perceptual similarity to the songs they are close to, according
to an audio similarity function, than non-hub songs. Application of
the recently introduced method of ``mutual proximity'' is able to
decisively improve this situation.
- OFAI-TR-2012-05 ( 1818kB PDF file)
Constructing high-level perceptual audio descriptors for textural sounds
- Thomas Grill
- This paper describes the construction of computable audio descriptors capable of modeling relevant high-level perceptual qualities of textural sounds. These qualities - all metaphoric bipolar and continuous constructs - have been identified in previous research: high-low, ordered-chaotic, smooth-coarse, tonal-noisy, and homogeneous-heterogeneous, covering timbral, temporal and structural properties of sound. We detail the construction of the descriptors and demonstrate the effects of tuning with respect to individual accuracy or mutual independence. The descriptors are evaluated on a corpus of 100 textural sounds against respective measures of human perception that have been retrieved by use of an online survey. Potential future use of perceptual audio descriptors in music creation is illustrated by a prototypic sound browser application.
Keywords: Music Information Retrieval, Audio descriptor, Perception
- This paper describes the construction of computable audio descriptors capable of modeling relevant high-level perceptual qualities of textural sounds. These qualities - all metaphoric bipolar and continuous constructs - have been identified in previous research: high-low, ordered-chaotic, smooth-coarse, tonal-noisy, and homogeneous-heterogeneous, covering timbral, temporal and structural properties of sound. We detail the construction of the descriptors and demonstrate the effects of tuning with respect to individual accuracy or mutual independence. The descriptors are evaluated on a corpus of 100 textural sounds against respective measures of human perception that have been retrieved by use of an online survey. Potential future use of perceptual audio descriptors in music creation is illustrated by a prototypic sound browser application.
- OFAI-TR-2012-04 ( 1973kB PDF file)
Visualization of perceptual qualities in textural sounds
- Thomas Grill, Arthur Flexer
- We describe a visualization strategy that is capable of efficiently representing relevant perceptual qualities of textural sounds. The general aim is to develop intuitive screen-based interfaces representing large collections of sounds, where sound retrieval shall be much facilitated by the exploitation of cross-modal mechanisms of human perception. We propose the use of metaphoric sensory properties that are shared between sounds and graphics, constructing a meaningful mapping of auditory to visual dimensions. For this purpose, we have implemented a visualization using tiled maps, essentially combining low-dimensional projection and iconic representation. To prove the suitability we show detailed results of experiments having been conducted in the form of an online survey. Potential future use in music creation is illustrated by a prototypic sound browser application.
Keywords: Music Information Retrieval, Visualization, Perception
- We describe a visualization strategy that is capable of efficiently representing relevant perceptual qualities of textural sounds. The general aim is to develop intuitive screen-based interfaces representing large collections of sounds, where sound retrieval shall be much facilitated by the exploitation of cross-modal mechanisms of human perception. We propose the use of metaphoric sensory properties that are shared between sounds and graphics, constructing a meaningful mapping of auditory to visual dimensions. For this purpose, we have implemented a visualization using tiled maps, essentially combining low-dimensional projection and iconic representation. To prove the suitability we show detailed results of experiments having been conducted in the form of an online survey. Potential future use in music creation is illustrated by a prototypic sound browser application.
- OFAI-TR-2012-03 ( 1633kB PDF file)
Emotional persistence in online chatting communities
- Antonios Garas, David Garcia, Marcin Skowron, Frank Schweitzer
- How do users behave in online chatrooms, where they instantaneously read and write posts? We analyzed about 2.5 million posts covering various topics in Internet relay channels, and found that user activity patterns follow known power-law and stretched exponential distributions, indicating that online chat activity is not different from other forms of communication. Analysing the emotional expressions (positive, negative, neutral) of users, we revealed a remarkable persistence both for individual users and channels. I.e. despite their anonymity, users tend to follow social norms in repeated interactions in online chats, which results in a specific emotional tone of the channels. We provide an agent-based model of emotional interaction, which recovers qualitatively both the activity patterns in chatrooms and the emotional persistence of users and channels. While our assumptions about agent's emotional expressions are rooted in psychology, the model allows to test different hypothesis regarding their emotional impact in online communication.
Keywords: Publications List Interact, applied physics, statistical physics, modelling and theory, text analysis, online communication, affective computing
- How do users behave in online chatrooms, where they instantaneously read and write posts? We analyzed about 2.5 million posts covering various topics in Internet relay channels, and found that user activity patterns follow known power-law and stretched exponential distributions, indicating that online chat activity is not different from other forms of communication. Analysing the emotional expressions (positive, negative, neutral) of users, we revealed a remarkable persistence both for individual users and channels. I.e. despite their anonymity, users tend to follow social norms in repeated interactions in online chats, which results in a specific emotional tone of the channels. We provide an agent-based model of emotional interaction, which recovers qualitatively both the activity patterns in chatrooms and the emotional persistence of users and channels. While our assumptions about agent's emotional expressions are rooted in psychology, the model allows to test different hypothesis regarding their emotional impact in online communication.
- OFAI-TR-2012-02 ( 337kB PDF file)
Creativity in Configuring Affective Agents for Interactive Storytelling
- Stefan Rank, Steve Hoffmann, Hans-Georg Struck, Ulrike Spierling, Paolo Petta
- Affective agent architectures can be used as control components in Interactive Storytelling systems for artificial autonomous characters. Creative authoring for such systems then involves configuration of these agents that translate part of the creative process to the systems runtime, necessarily constrained by the capabilities of the specific implementation. Using a framework for presenting configuration options based on literature review; a questionnaire evaluation of authors preferences for character creation; and a case study of an authors conceptualisation of the creative process, we categorise available and potential methods for configuring affective agents in existing systems regarding creative exploration. Finally, we present work-in-progress on exemplifying the different options in the ActAffAct system.
Keywords: Creativity, Authoring, Interactive Storytelling, Affective Characters
- Affective agent architectures can be used as control components in Interactive Storytelling systems for artificial autonomous characters. Creative authoring for such systems then involves configuration of these agents that translate part of the creative process to the systems runtime, necessarily constrained by the capabilities of the specific implementation. Using a framework for presenting configuration options based on literature review; a questionnaire evaluation of authors preferences for character creation; and a case study of an authors conceptualisation of the creative process, we categorise available and potential methods for configuring affective agents in existing systems regarding creative exploration. Finally, we present work-in-progress on exemplifying the different options in the ActAffAct system.
- OFAI-TR-2012-01 ( 399kB PDF file)
Towards the development of a conceptual framework for an applied theory of problem structuring for complex agents: Questions to Luhmann's Social System Theory
- Karl Neumayer, Paolo Petta
- This extended abstract provides a snapshot of the current status of our efforts aimed at the development of a principled approach to corporate strategy consulting. This research is motivated by the need to improve the quality of strategic decision making of enterprises as complex agents. To this end, we take a step back and propose a paradigmatic reconceptualisation of the foundations of decision making in terms of processes underlying Problem Structuring, with implications in particular for the identity of complex agents, the notion of rationality, as well as the shaping of decision processes. The two interrelated main components are the transpersonal Weinhaus conceptual modelling framework and a structured method for the development, implementation, and verification of sound interventions. A key guideline is our aim to enable the identification of relevant, practical, and verifiable interventions. Against this body of work, we can formulate a number of candidate questions to Social Systems Theory to discuss at the Symposium, so as to: critically review our achievements and ascertain the scope of applicability of our model, identify directions and means of improvements, look for answers to open challenges, and understand the potential for a reformulation in Social Systems Theory terms.
Keywords: Corporate strategy consulting, Enterprise modelling, Transpersonal modelling, Action theory, Theory of social systems, Agent-based modelling, Business modelling,
(Extended version of the extended abstract appearing in the proceedings of the 21st European Meeting on Cybernetics and Systems Research (EMCSR 2012), April 10-13, Vienna, Austria (EU), BCSSS Bertalanffy Center for the Study of Systems Science, Vienna, Austria (EU)) - This extended abstract provides a snapshot of the current status of our efforts aimed at the development of a principled approach to corporate strategy consulting. This research is motivated by the need to improve the quality of strategic decision making of enterprises as complex agents. To this end, we take a step back and propose a paradigmatic reconceptualisation of the foundations of decision making in terms of processes underlying Problem Structuring, with implications in particular for the identity of complex agents, the notion of rationality, as well as the shaping of decision processes. The two interrelated main components are the transpersonal Weinhaus conceptual modelling framework and a structured method for the development, implementation, and verification of sound interventions. A key guideline is our aim to enable the identification of relevant, practical, and verifiable interventions. Against this body of work, we can formulate a number of candidate questions to Social Systems Theory to discuss at the Symposium, so as to: critically review our achievements and ascertain the scope of applicability of our model, identify directions and means of improvements, look for answers to open challenges, and understand the potential for a reformulation in Social Systems Theory terms.