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|Acronym=CEC 2021 | |Acronym=CEC 2021 | ||
|Title=IEEE Congress on Evolutionary Computation | |Title=IEEE Congress on Evolutionary Computation | ||
| + | |In Event Series=Event Series:CEC | ||
| + | |Single Day Event=no | ||
| + | |Start Date=2021/06/28 | ||
| + | |End Date=2021/07/01 | ||
| + | |Event Status=as scheduled | ||
| + | |Event Mode=online | ||
| + | |Academic Field=Evolutionary Computation | ||
| + | |Official Website=https://cec2021.mini.pw.edu.pl/ | ||
|Type=Congress | |Type=Congress | ||
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|Twitter account=@cec2021 | |Twitter account=@cec2021 | ||
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|wikicfpId=109308 | |wikicfpId=109308 | ||
|pageCreator=User:Curator 53 | |pageCreator=User:Curator 53 | ||
|pageEditor=User:Curator 53 | |pageEditor=User:Curator 53 | ||
|contributionType=1 | |contributionType=1 | ||
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}} | }} | ||
| − | ==== Topics ==== | + | {{Event Deadline |
| + | |Notification Deadline=2021/04/06 | ||
| + | |Paper Deadline=2021/02/23 | ||
| + | |Submission Deadline=2021/02/21 | ||
| + | }} | ||
| + | {{Organizer | ||
| + | |Contributor Type=organization | ||
| + | |Organization=IEEE Computational Intelligence Society, Institute of Electrical and Electronics Engineers | ||
| + | }} | ||
| + | {{Event Metric}} | ||
| + | {{S Event}} | ||
| + | ====Topics==== | ||
The Conference Organizing Committee invites submissions of original, previously unpublished innovative research in any topic of evolutionary computation including, but not limited to: | The Conference Organizing Committee invites submissions of original, previously unpublished innovative research in any topic of evolutionary computation including, but not limited to: | ||
| − | ===== Algorithms ===== | + | =====Algorithms===== |
| − | * | + | *Adaptive dynamic programming and reinforcement learning |
| − | * | + | *Ant colony optimization and Swarm Intelligence |
| − | * | + | *Artificial immune systems |
| − | * | + | *Coevolutionary systems |
| − | * | + | *Coevolution and collective behavior |
| − | * | + | *Convergence, scalability and complexity analysis |
| − | * | + | *Cultural algorithms |
| − | * | + | *Differential evolution |
| − | * | + | *Estimation of distribution algorithms |
| − | * | + | *Evolutionary computation theory |
| − | * | + | *Evolutionary programming |
| − | * | + | *Evolution strategies |
| − | * | + | *Genetic algorithms |
| − | * | + | *Genetic programming |
| − | * | + | *Heuristics, metaheuristics and hyper-heuristics |
| − | * | + | *Interactive evolutionary computation |
| − | * | + | *Learning classifier systems |
| − | * | + | *Memetic, multi-meme and hybrid algorithms |
| − | * | + | *Molecular and quantum computing |
| − | * | + | *Multi-objective evolutionary algorithms |
| − | * | + | *Parallel and distributed algorithms |
| − | * | + | *Particle swarm optimization |
| − | * | + | *Representation and operators |
| − | * | + | *Self-adaptation in evolutionary computation |
| − | * | + | *Theory and Implementation |
| − | ===== Hybrid Systems of Computational Intelligence ===== | + | =====Hybrid Systems of Computational Intelligence===== |
| − | * | + | *Evolved neural networks |
| − | * | + | *Evolutionary fuzzy systems |
| − | * | + | *Evolved neuro-fuzzy systems |
| − | ===== Optimization ===== | + | =====Optimization===== |
| − | * | + | *Combinatorial Optimization and Metaheuristics |
| − | * | + | *Constraint handling |
| − | * | + | *Discrete and combinatorial optimization |
| − | * | + | *Dynamic and uncertain environments |
| − | * | + | *Meta-modeling and surrogate models |
| − | * | + | *Evolutionary simulation-based optimization |
| − | * | + | *Preference handling |
| − | * | + | *Large-scale problems |
| − | * | + | *Multi objective optimization |
| − | * | + | *Numerical optimization |
| − | ===== Related Areas and Applications ===== | + | =====Related Areas and Applications===== |
| − | * | + | *Art and music |
| − | * | + | *Artificial ecology and artificial life |
| − | * | + | *Autonomous mental and behavior development |
| − | * | + | *Biometrics, bioinformatics and biomedical applications |
| − | * | + | *Classification, clustering and data analysis |
| − | * | + | *Data mining |
| − | * | + | *Defense and cybersecurity |
| − | * | + | *Evolutionary games and multi-agent systems |
| − | * | + | *Evolutionary Machine Learning |
| − | * | + | *Evolvable hardware and software |
| − | * | + | *Evolutionary Robotics |
| − | * | + | *Engineering applications |
| − | * | + | *Emergent technologies |
| − | * | + | *Finance and economics |
| − | * | + | *Games |
| − | * | + | *Intelligent systems applications |
| − | * | + | *Robotics |
| − | * | + | *Real-world applications |
Latest revision as of 12:46, 9 May 2023
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Venue
Warning: Venue is missing. The map might not show the exact location.
Topics
The Conference Organizing Committee invites submissions of original, previously unpublished innovative research in any topic of evolutionary computation including, but not limited to:
Algorithms
- Adaptive dynamic programming and reinforcement learning
- Ant colony optimization and Swarm Intelligence
- Artificial immune systems
- Coevolutionary systems
- Coevolution and collective behavior
- Convergence, scalability and complexity analysis
- Cultural algorithms
- Differential evolution
- Estimation of distribution algorithms
- Evolutionary computation theory
- Evolutionary programming
- Evolution strategies
- Genetic algorithms
- Genetic programming
- Heuristics, metaheuristics and hyper-heuristics
- Interactive evolutionary computation
- Learning classifier systems
- Memetic, multi-meme and hybrid algorithms
- Molecular and quantum computing
- Multi-objective evolutionary algorithms
- Parallel and distributed algorithms
- Particle swarm optimization
- Representation and operators
- Self-adaptation in evolutionary computation
- Theory and Implementation
Hybrid Systems of Computational Intelligence
- Evolved neural networks
- Evolutionary fuzzy systems
- Evolved neuro-fuzzy systems
Optimization
- Combinatorial Optimization and Metaheuristics
- Constraint handling
- Discrete and combinatorial optimization
- Dynamic and uncertain environments
- Meta-modeling and surrogate models
- Evolutionary simulation-based optimization
- Preference handling
- Large-scale problems
- Multi objective optimization
- Numerical optimization
Related Areas and Applications
- Art and music
- Artificial ecology and artificial life
- Autonomous mental and behavior development
- Biometrics, bioinformatics and biomedical applications
- Classification, clustering and data analysis
- Data mining
- Defense and cybersecurity
- Evolutionary games and multi-agent systems
- Evolutionary Machine Learning
- Evolvable hardware and software
- Evolutionary Robotics
- Engineering applications
- Emergent technologies
- Finance and economics
- Games
- Intelligent systems applications
- Robotics
- Real-world applications
