CALL FOR PAPERS

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Scope of the conference

Adaptation plays a central role in dynamically changing systems. It is about the ability of the system to "responsively" self-adjust upon change in the surrounding environment. Like in living creatures that have evolved over millions of years developing ecological systems due to their self-adaptation and fitness capacity to the dynamic environment, systems undergo similar cycle to improve or at least do not weaken their performance when internal or external changes take place. Internal or endogenous change bears on the physical structure of the system (hardware and/or software components) due mainly to faults, knowledge inconsistency, etc. It requires a certain number of adaptivity features such as flexible deployment, self-testing, self-healing and self-correction. Extraneous change touches on the environment implication like operational mode or regime, non-stationarity of input, new knowledge facts, need to cooperation with other systems, etc. These two classes of change shed light on the research avenues towards smart systems. To meet the challenges of these systems, a sustainable effort is necessary to develop: (1) adequate operational structures involving notions like self-healing, self-testing, reconfiguration, optimal software and hardware synergy, etc.; (2) appropriate design concepts encompassing self-x properties (self-organization, self-monitoring, etc.) to allow for autonomy and optimal behavior in the (dynamically changing) environment; (3) efficient computational algorithms targetting dynamic setting, life-long learning, evolving and adaptive behavior and structure. For the sake of this three-fold development direction, various design and computational models stemming from machine learning, statistics, metaphors of nature inspired from biological and cognitive plausibility, etc. can be of central relevance. ICAIS intends to be a forum for researchers and practitioners to discuss the recent advances of adaptive and intelligent systems with respect to the three research directions and their application in various practical domains. Target topics (but not limited to) are:

Track 1: Self-X Systems

Self-adaptation
Self-organization and behavior emergence
Self-managing
Self-healing
Self-monitoring
Multi-agent systems
Self-X software agents
Self-X robots
Self-organizing sensor networks
Evolving systems

Track 2: Incremental Learning

Online incremental learning
Self-growing neural networks
Adaptive and life-long learning
Plasticity and stability
Forgetting
Unlearning
Novelty detection
Perception and evolution
Drift handling
Adaptation in changing environments

Track 3: Online Processing

Adaptive rule-based systems
Adaptive identification systems
Adaptive decision systems
Adaptive preference learning
Time series prediction
Online and single-pass data mining
Online classification
Online clustering
Online regression
Online feature selection and reduction
Online information routing

Track 4: Dynamic and Evolving Models in Computational Intelligence

(Dynamic) Neural networks architectures
(Dynamic) Evolutionary computation
(Dynamic) Swarm intelligence
(Dynamic) Immune and bacterial systems
Uncertainty and fuzziness modeling for adaptation
Approximate reasoning and adaptation
Chaotic systems

Track 5: Software & System Engineering

Autonomic computing
Organic computing
Evolution
Adaptive software architecture
Software change
Software agents
Engineering of complex systems
Adaptive software engineering processes
Component-based development

Track 6: Applications - Adaptivity and learning in

Smart systems
Ambient / ubiquitous environments
Distributed intelligence
Robotics
Industrial applications
Internet applications
Business applications
Supply chain management
etc.