|
Showing 1 - 15 of
15 matches in All Departments
|
Advances in Computational Collective Intelligence - 15th International Conference, ICCCI 2023, Budapest, Hungary, September 27–29, 2023, Proceedings (1st ed. 2023)
Ngoc Thanh Nguyen, János Botzheim, László Gulyás, Manuel Nunez, Jan Treur, …
|
R3,296
Discovery Miles 32 960
|
Ships in 10 - 15 working days
|
This book constitutes the refereed proceedings of the 15th
International Conference on Advances in Computational
Collective Intelligence,  ICCCI 2023, held in Budapest,
Hungary, during September 27–29, 2023.
The 59 full papers included in this book were carefully
reviewed and selected from 218 submissions. They
were organized in topical sections as follows:Â Collective
Intelligence and Collective Decision-Making, Deep Learning
Techniques,  Natural Language Processing, Data
Minning and Machine learning, Social Networks and Speek
Communication, Cybersecurity and Internet of
Things, Cooperative Strategies for Decision Making and
Optimization, Digital Content Understanding and Apllication
for Industry 4.0 and Computational Intelligence in Medical
Applications.
This book addresses the challenging topic of modeling adaptive
networks, which often manifest inherently complex behavior.
Networks by themselves can usually be modeled using a neat,
declarative, and conceptually transparent Network-Oriented Modeling
approach. In contrast, adaptive networks are networks that change
their structure; for example, connections in Mental Networks
usually change due to learning, while connections in Social
Networks change due to various social dynamics. For adaptive
networks, separate procedural specifications are often added for
the adaptation process. Accordingly, modelers have to deal with a
less transparent, hybrid specification, part of which is often more
at a programming level than at a modeling level. This book presents
an overall Network-Oriented Modeling approach that makes designing
adaptive network models much easier, because the adaptation
process, too, is modeled in a neat, declarative, and conceptually
transparent Network-Oriented Modeling manner, like the network
itself. Thanks to this approach, no procedural, algorithmic, or
programming skills are needed to design complex adaptive network
models. A dedicated software environment is available to run these
adaptive network models from their high-level specifications.
Moreover, because adaptive networks are described in a network
format as well, the approach can simply be applied iteratively, so
that higher-order adaptive networks in which network adaptation
itself is adaptive (second-order adaptation), too can be modeled
just as easily. For example, this can be applied to model
metaplasticity in cognitive neuroscience, or second-order
adaptation in biological and social contexts. The book illustrates
the usefulness of this approach via numerous examples of complex
(higher-order) adaptive network models for a wide variety of
biological, mental, and social processes. The book is suitable for
multidisciplinary Master's and Ph.D. students without assuming much
prior knowledge, although also some elementary mathematical
analysis is involved. Given the detailed information provided, it
can be used as an introduction to Network-Oriented Modeling for
adaptive networks. The material is ideally suited for teaching
undergraduate and graduate students with multidisciplinary
backgrounds or interests. Lecturers will find additional material
such as slides, assignments, and software.
|
Advances in Computational Collective Intelligence - 13th International Conference, ICCCI 2021, Kallithea, Rhodes, Greece, September 29 - October 1, 2021, Proceedings (Paperback, 1st ed. 2021)
Krystian Wojtkiewicz, Jan Treur, Elias Pimenidis, Marcin Maleszka
|
R3,614
Discovery Miles 36 140
|
Ships in 10 - 15 working days
|
This book constitutes refereed proceedings of the 13th
International Conference on International Conference on
Computational Collective Intelligence, ICCCI 2021, held in
Kallithea, Rhodes, Greece, in October - November 2021. Due to the
the COVID-19 pandemic the conference was held online. The 44 full
papers and 14 short papers were thoroughly reviewed and selected
from 231 submissions. The papers are organized according to the
following topical sections: social networks and recommender
systems; collective decision-making; computer vision techniques;
innovations in intelligent systems; cybersecurity intelligent
methods; data mining and machine learning; machine learning in
real-world data; Internet of Things and computational technologies
for collective intelligence; smart industry and management systems;
low resource languages processing; computational intelligence for
multimedia understanding.
This book addresses the challenging topic of modeling adaptive
networks, which often manifest inherently complex behavior.
Networks by themselves can usually be modeled using a neat,
declarative, and conceptually transparent Network-Oriented Modeling
approach. In contrast, adaptive networks are networks that change
their structure; for example, connections in Mental Networks
usually change due to learning, while connections in Social
Networks change due to various social dynamics. For adaptive
networks, separate procedural specifications are often added for
the adaptation process. Accordingly, modelers have to deal with a
less transparent, hybrid specification, part of which is often more
at a programming level than at a modeling level. This book presents
an overall Network-Oriented Modeling approach that makes designing
adaptive network models much easier, because the adaptation
process, too, is modeled in a neat, declarative, and conceptually
transparent Network-Oriented Modeling manner, like the network
itself. Thanks to this approach, no procedural, algorithmic, or
programming skills are needed to design complex adaptive network
models. A dedicated software environment is available to run these
adaptive network models from their high-level specifications.
Moreover, because adaptive networks are described in a network
format as well, the approach can simply be applied iteratively, so
that higher-order adaptive networks in which network adaptation
itself is adaptive (second-order adaptation), too can be modeled
just as easily. For example, this can be applied to model
metaplasticity in cognitive neuroscience, or second-order
adaptation in biological and social contexts. The book illustrates
the usefulness of this approach via numerous examples of complex
(higher-order) adaptive network models for a wide variety of
biological, mental, and social processes. The book is suitable for
multidisciplinary Master's and Ph.D. students without assuming much
prior knowledge, although also some elementary mathematical
analysis is involved. Given the detailed information provided, it
can be used as an introduction to Network-Oriented Modeling for
adaptive networks. The material is ideally suited for teaching
undergraduate and graduate students with multidisciplinary
backgrounds or interests. Lecturers will find additional material
such as slides, assignments, and software.
This book introduces a generic approach to model the use and
adaptation of mental models, including the control over this. In
their mental processes, humans often make use of internal mental
models as a kind of blueprints for processes that can take place in
the world or in other persons. By internal mental simulation of
such a mental model in their brain, they can predict and be
prepared for what can happen in the future. Usually, mental models
are adaptive: they can be learned, refined, revised, or forgotten,
for example. Although there is a huge literature on mental models
in various disciplines, a systematic account of how to model them
computationally in a transparent manner is lacking. This approach
allows for computational modeling of humans using mental models
without a need for any algorithmic or programming skills, allowing
for focus on the process of conceptualizing, modeling, and
simulating complex, real-world mental processes and behaviors. The
book is suitable for and is used as course material for
multidisciplinary Master and Ph.D. students.
|
Computational Collective Intelligence - 15th International Conference, ICCCI 2023, Budapest, Hungary, September 27–29, 2023, Proceedings (1st ed. 2023)
Ngoc Thanh Nguyen, János Botzheim, László Gulyás, Manuel Nunez, Jan Treur, …
|
R2,637
Discovery Miles 26 370
|
Ships in 12 - 17 working days
|
This book constitutes the refereed proceedings of the 15th
International Conference on Computational Collective
Intelligence,  ICCCI 2023, held in Budapest,
Hungary, during September 27–29, 2023. The 63 full papers
included in this book were carefully reviewed and selected
from 218 submissions. They are organized in topical
sections as follows: collective intelligence and collective
decision-making; deep learning techniques;Â natural language
processing; data mining and machine learning; social networks and
intelligent systems; cybersecurity, blockchain technology and
Internet of Things; cooperative strategies for decision making and
optimization; computational intelligence for digital content
understanding;Â knowledge engineering and application for
Industry 4.0; computational intelligence in medical applications;
and ensemble models and data fusion.
Since its origination in the mid-twentieth century, the area of
Artificial Intelligence (AI) has undergone a number of
developments. While the early interest in AI was mainly triggered
by the desire to develop artifacts that show the same intelligent
behavior as humans, nowadays scientists have realized that research
in AI involves a multitude of separate challenges, besides the
traditional goal to replicate human intelligence. In particular,
recent history has pointed out that a variety of 'intelligent'
computational techniques, part of which are inspired by human
intelligence, may be successfully applied to solve all kinds of
practical problems. This sub-area of AI, which has its main
emphasis on applications of intelligent systems to solve real-life
problems, is currently known under the term Applied Intelligence.
The objective of the International Conference on Industrial,
Engineering & Other Applications of Applied Intelligent Systems
(IEA/AIE) is to promote and disseminate recent research
developments in Applied Intelligence. The current book contains 30
chapters authored by participants of the 26th edition of IEA/AIE,
which was held in Amsterdam, the Netherlands. The material of each
chapter is self-contained and was reviewed by at least two
anonymous referees, to assure a high quality. Readers can select
any individual chapter based on their research interests without
the need of reading other chapters. We are confident that this book
provides useful reference values to researchers and students in the
field of Applied Intelligence, enabling them to find opportunities
and recognize challenges in the field.
Since its origination in the mid-twentieth century, the area of
Artificial Intelligence (AI) has undergone a number of
developments. While the early interest in AI was mainly triggered
by the desire to develop artifacts that show the same intelligent
behavior as humans, nowadays scientists have realized that research
in AI involves a multitude of separate challenges, besides the
traditional goal to replicate human intelligence. In particular,
recent history has pointed out that a variety of 'intelligent'
computational techniques, part of which are inspired by human
intelligence, may be successfully applied to solve all kinds of
practical problems. This sub-area of AI, which has its main
emphasis on applications of intelligent systems to solve real-life
problems, is currently known under the term Applied Intelligence.
The objective of the International Conference on Industrial,
Engineering & Other Applications of Applied Intelligent Systems
(IEA/AIE) is to promote and disseminate recent research
developments in Applied Intelligence. The current book contains 30
chapters authored by participants of the 26th edition of IEA/AIE,
which was held in Amsterdam, the Netherlands. The material of each
chapter is self-contained and was reviewed by at least two
anonymous referees, to assure a high quality. Readers can select
any individual chapter based on their research interests without
the need of reading other chapters. We are confident that this book
provides useful reference values to researchers and students in the
field of Applied Intelligence, enabling them to find opportunities
and recognize challenges in the field.
|
Recent Trends in Applied Artificial Intelligence - 26th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2013, Amsterdam, The Netherlands, June 17-21, 2013, Proceedings (Paperback, 2013 ed.)
Moonis Ali, Tibor Bosse, Koen V. Hindriks, Mark Hoogendoorn, Catholijn M. Jonker, …
|
R1,691
Discovery Miles 16 910
|
Ships in 10 - 15 working days
|
This volume constitutes the thoroughly refereed conference
proceedings of the 26th International Conference on Industrial
Engineering and Other Applications of Applied Intelligence Systems,
IEA/AIE 2013, held in Amsterdam, The Netherlands, in June 2013. The
total of 71 papers selected for the proceedings were carefully
reviewed and selected from 185 submissions. The papers focus on the
following topics: auctions and negotiation, cognitive modeling,
crowd behavior modeling, distributed systems and networks,
evolutionary algorithms, knowledge representation and reasoning,
pattern recognition, planning, problem solving, robotics, text
mining, advances in recommender systems, business process
intelligence, decision support for safety-related systems,
innovations in intelligent computation and applications,
intelligent image and signal processing, and machine learning
methods applied to manufacturing processes and production systems.
This volume, the 6th volume in the DRUMS Handbook series, is part
of the after math of the successful ESPRIT project DRUMS
(Defeasible Reasoning and Un certainty Management Systems) which
took place in two stages from 1989-1996. In the second stage
(1993-1996) a work package was introduced devoted to the topics
Reasoning and Dynamics, covering both the topics of 'Dynamics of
Rea soning', where reasoning is viewed as a process, and 'Reasoning
about Dynamics', which must be understood as pertaining to how both
designers of and agents within dynamic systems may reason about
these systems. The present volume presents work done in this
context. This work has an emphasis on modelling and formal
techniques in the investigation of the topic "Reasoning and
Dynamics," but it is not mere theory that occupied us. Rather
research was aimed at bridging the gap between theory and practice.
Therefore also real-life applications of the modelling techniques
were considered, and we hope this also shows in this volume, which
is focused on the dynamics of reasoning processes. In order to give
the book a broader perspective, we have invited a number of
well-known researchers outside the project but working on similar
topics to contribute as well. We have very pleasant recollections
of the project, with its lively workshops and other meetings, with
the many sites and researchers involved, both within and outside
our own work package."
This volume, the 7th volume in the DRUMS Handbook series, is part
of the aftermath of the successful ESPRIT project DRUMS (Defeasible
Reasoning and Uncertainty Management Systems) which took place in
two stages from 1989- 1996. In the second stage (1993-1996) a work
package was introduced devoted to the topics Reasoning and
Dynamics, covering both the topics of "Dynamics of Reasoning,"
where reasoning is viewed as a process, and "Reasoning about
Dynamics," which must be understood as pertaining to how both
designers of and agents within dynamic systems may reason about
these systems. The present volume presents work done in this
context extended with some work done by outstanding researchers
outside the project on related issues. While the previous volume in
this series had its focus on the dynamics of reasoning pro cesses,
the present volume is more focused on "reasoning about dynamics',
viz. how (human and artificial) agents reason about (systems in)
dynamic environments in order to control them. In particular we
consider modelling frameworks and generic agent models for
modelling these dynamic systems and formal approaches to these
systems such as logics for agents and formal means to reason about
agent based and compositional systems, and action & change more
in general. We take this opportunity to mention that we have very
pleasant recollections of the project, with its lively workshops
and other meetings, with the many sites and researchers involved,
both within and outside our own work package."
This volume, the 7th volume in the DRUMS Handbook series, is part
of the aftermath of the successful ESPRIT project DRUMS (Defeasible
Reasoning and Uncertainty Management Systems) which took place in
two stages from 1989- 1996. In the second stage (1993-1996) a work
package was introduced devoted to the topics Reasoning and
Dynamics, covering both the topics of "Dynamics of Reasoning,"
where reasoning is viewed as a process, and "Reasoning about
Dynamics," which must be understood as pertaining to how both
designers of and agents within dynamic systems may reason about
these systems. The present volume presents work done in this
context extended with some work done by outstanding researchers
outside the project on related issues. While the previous volume in
this series had its focus on the dynamics of reasoning pro cesses,
the present volume is more focused on "reasoning about dynamics',
viz. how (human and artificial) agents reason about (systems in)
dynamic environments in order to control them. In particular we
consider modelling frameworks and generic agent models for
modelling these dynamic systems and formal approaches to these
systems such as logics for agents and formal means to reason about
agent based and compositional systems, and action & change more
in general. We take this opportunity to mention that we have very
pleasant recollections of the project, with its lively workshops
and other meetings, with the many sites and researchers involved,
both within and outside our own work package."
This volume, the 6th volume in the DRUMS Handbook series, is part
of the after math of the successful ESPRIT project DRUMS
(Defeasible Reasoning and Un certainty Management Systems) which
took place in two stages from 1989-1996. In the second stage
(1993-1996) a work package was introduced devoted to the topics
Reasoning and Dynamics, covering both the topics of 'Dynamics of
Rea soning', where reasoning is viewed as a process, and 'Reasoning
about Dynamics', which must be understood as pertaining to how both
designers of and agents within dynamic systems may reason about
these systems. The present volume presents work done in this
context. This work has an emphasis on modelling and formal
techniques in the investigation of the topic "Reasoning and
Dynamics," but it is not mere theory that occupied us. Rather
research was aimed at bridging the gap between theory and practice.
Therefore also real-life applications of the modelling techniques
were considered, and we hope this also shows in this volume, which
is focused on the dynamics of reasoning processes. In order to give
the book a broader perspective, we have invited a number of
well-known researchers outside the project but working on similar
topics to contribute as well. We have very pleasant recollections
of the project, with its lively workshops and other meetings, with
the many sites and researchers involved, both within and outside
our own work package."
This book introduces a generic approach to model the use and
adaptation of mental models, including the control over this. In
their mental processes, humans often make use of internal mental
models as a kind of blueprints for processes that can take place in
the world or in other persons. By internal mental simulation of
such a mental model in their brain, they can predict and be
prepared for what can happen in the future. Usually, mental models
are adaptive: they can be learned, refined, revised, or forgotten,
for example. Although there is a huge literature on mental models
in various disciplines, a systematic account of how to model them
computationally in a transparent manner is lacking. This approach
allows for computational modeling of humans using mental models
without a need for any algorithmic or programming skills, allowing
for focus on the process of conceptualizing, modeling, and
simulating complex, real-world mental processes and behaviors. The
book is suitable for and is used as course material for
multidisciplinary Master and Ph.D. students.
|
Advances in Computational Collective Intelligence - 14th International Conference, ICCCI 2022, Hammamet, Tunisia, September 28-30, 2022, Proceedings (Paperback, 1st ed. 2022)
Costin Badica, Jan Treur, Djamal Benslimane, Bogumila Hnatkowska, Marek Krotkiewicz
|
R3,104
Discovery Miles 31 040
|
Ships in 10 - 15 working days
|
This book constitutes refereed proceedings of the 14th
International Conference on International Conference on
Computational Collective Intelligence, ICCCI 2022, held in
Hammamet, Tunisia, in September 2022. The 43 full papers and 15
short papers were thoroughly reviewed and selected from 421
submissions. The papers are grouped in topical sections on
collective intelligence and collective decision-making; natural
language processing; deep learning; computational intelligence for
multimedia understanding; computational intelligence in medical
applications; applications for industry 4.0; experience enhanced
intelligence to IoT and sensors; cooperative strategies for
decision making and optimization; machine learning methods.
|
You may like...
Loot
Nadine Gordimer
Paperback
(2)
R398
R330
Discovery Miles 3 300
|