57,851 research outputs found
A formal model of emotional-response, inspired from human cognition and emotion systems
In this paper, we used the formalisms of decision-making theory and theories in psychology, physiology and cognition to proposing a macro model of human emotional-response. We believe that using such formalism can fill the gap between psychology, cognitive science and AI, and can be useful in the design of human-like agents.
This model can be used in a wide variety of applications such as artificial agents, user interface, and intelligent tutoring systems. Using the proposed model, we can provide for human behaviors like mood, personality and biological response in machines. This capability will enable such systems, to adapt their responses and behaviors. In situations where there are multiple ways for performing an action, this model can help with the decision making process
Memories for Life: A Review of the Science and Technology
This paper discusses scientific, social and technological aspects of memory. Recent developments in our understanding of memory processes and mechanisms, and their digital implementation, have placed the encoding, storage, management and retrieval of information at the forefront of several fields of research. At the same time, the divisions between the biological, physical and the digital worlds seem to be dissolving. Hence opportunities for interdisciplinary research into memory are being created, between the life sciences, social sciences and physical sciences. Such research may benefit from immediate application into information management technology as a testbed. The paper describes one initiative, Memories for Life, as a potential common problem space for the various interested disciplines
What is Computational Intelligence and where is it going?
What is Computational Intelligence (CI) and what are its relations with Artificial Intelligence (AI)? A brief survey of the scope of CI journals and books with ``computational intelligence'' in their title shows that at present it is an umbrella for three core technologies (neural, fuzzy and evolutionary), their applications, and selected fashionable pattern recognition methods. At present CI has no comprehensive foundations and is more a bag of tricks than a solid branch of science. The change of focus from methods to challenging problems is advocated, with CI defined as a part of computer and engineering sciences devoted to solution of non-algoritmizable problems. In this view AI is a part of CI focused on problems related to higher cognitive functions, while the rest of the CI community works on problems related to perception and control, or lower cognitive functions. Grand challenges on both sides of this spectrum are addressed
Human Computation and Convergence
Humans are the most effective integrators and producers of information,
directly and through the use of information-processing inventions. As these
inventions become increasingly sophisticated, the substantive role of humans in
processing information will tend toward capabilities that derive from our most
complex cognitive processes, e.g., abstraction, creativity, and applied world
knowledge. Through the advancement of human computation - methods that leverage
the respective strengths of humans and machines in distributed
information-processing systems - formerly discrete processes will combine
synergistically into increasingly integrated and complex information processing
systems. These new, collective systems will exhibit an unprecedented degree of
predictive accuracy in modeling physical and techno-social processes, and may
ultimately coalesce into a single unified predictive organism, with the
capacity to address societies most wicked problems and achieve planetary
homeostasis.Comment: Pre-publication draft of chapter. 24 pages, 3 figures; added
references to page 1 and 3, and corrected typ
Digital Ecosystems: Ecosystem-Oriented Architectures
We view Digital Ecosystems to be the digital counterparts of biological
ecosystems. Here, we are concerned with the creation of these Digital
Ecosystems, exploiting the self-organising properties of biological ecosystems
to evolve high-level software applications. Therefore, we created the Digital
Ecosystem, a novel optimisation technique inspired by biological ecosystems,
where the optimisation works at two levels: a first optimisation, migration of
agents which are distributed in a decentralised peer-to-peer network, operating
continuously in time; this process feeds a second optimisation based on
evolutionary computing that operates locally on single peers and is aimed at
finding solutions to satisfy locally relevant constraints. The Digital
Ecosystem was then measured experimentally through simulations, with measures
originating from theoretical ecology, evaluating its likeness to biological
ecosystems. This included its responsiveness to requests for applications from
the user base, as a measure of the ecological succession (ecosystem maturity).
Overall, we have advanced the understanding of Digital Ecosystems, creating
Ecosystem-Oriented Architectures where the word ecosystem is more than just a
metaphor.Comment: 39 pages, 26 figures, journa
Managed Forgetting to Support Information Management and Knowledge Work
Trends like digital transformation even intensify the already overwhelming
mass of information knowledge workers face in their daily life. To counter
this, we have been investigating knowledge work and information management
support measures inspired by human forgetting. In this paper, we give an
overview of solutions we have found during the last five years as well as
challenges that still need to be tackled. Additionally, we share experiences
gained with the prototype of a first forgetful information system used 24/7 in
our daily work for the last three years. We also address the untapped potential
of more explicated user context as well as features inspired by Memory
Inhibition, which is our current focus of research.Comment: 10 pages, 2 figures, preprint, final version to appear in KI -
K\"unstliche Intelligenz, Special Issue: Intentional Forgettin
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