posted by user: sebastianrisi || 4040 views || tracked by 7 users: [display]

GECCO GDS 2014 : Generative and Developmental Systems (GDS) track at GECCO 2014

FacebookTwitterLinkedInGoogle

Link: http://www.sigevo.org/gecco-2014/
 
When Jul 12, 2014 - Jul 16, 2014
Where Vancouver, Canada
Abstract Registration Due Jan 15, 2014
Submission Deadline Jan 29, 2014
Notification Due Mar 12, 2014
Final Version Due Apr 14, 2014
Categories    evolutionary computation   artificial intelligence   machine learning   computer sciences
 

Call For Papers

***************************************************************************

*** CALL FOR PAPERS
*** 2014 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO-2014)
*** Generative and Developmental Systems (GDS) Track
*** July 12-16, 2014 in Vancouver, BC, Canada
*** Organized by ACM SIGEVO
*** http://www.sigevo.org/gecco-2014
*************************************************************************

We invite you to submit your paper to the Generative and Developmental Systems (GDS) track at GECCO 2014. The focus of the GDS track is making artificially evolved systems scale to high complexity, with work ranging from biologically inspired approaches to automated engineering design. Each paper submitted to the GDS Track will be reviewed by experts in the field. The size and prestige of the GECCO conference will allow many researchers to learn about your work, both at the conference and via the proceedings (GECCO has the highest impact rating of all conferences in the field of Evolutionary Computation and Artificial Life).

TRACK DESCRIPTION
---------------------------

As artificial systems (of hardware, software and networks) continue to grow in size and complexity, the engineering traditions of rigid top-down planning and control are reaching the limits of their applicability. In contrast, biological evolution is responsible for the apparently unbounded complexity and diversity of living organisms. Yet, over 150 years after Darwin's and Mendel's work, and the subsequent "Modern Synthesis" of evolution and genetics, the developmental process that maps genotype to phenotype is still poorly understood. Understanding the evolution of complex systems - large sets of elements interacting locally and giving rise to collective behavior - will help us create a new generation of truly autonomous and adaptive artificial systems. The Generative and Developmental Systems (GDS) track seeks to unlock the full potential of in silico evolution as a design methodology that can "scale up" to systems of great complexity, meeting our specifications with minimal manual programming effort. Both qualitative and quantitative advances toward this long-term goal will be welcomed.

Indirect and open-ended representations: The genotype is more than the information needed to produce a single individual. It is a layered repository of many generations of evolutionary innovation, shaped by two requirements: to be fit in the short term, and to be evolvable over the long term through its influence on the production of variation. "Indirect representations" such as morphogenesis or string-rewriting grammars, which rely on developmental or generative processes, may allow long-term improvements to the "genetic architecture" via accumulated layers of elaboration, and emergent new features. In contrast, "direct representations" are not capable of open-ended elaboration because they are restricted to predefined features.

Complex environments encourage complex phenotypes: While complex genotypes may not be required for success in simple environments, they may enable unprecedented phenotypes and behaviors that can later successfully invade new, uncrowded niches in complex environments; this can create pressure toward increasing complexity over the long term. Many factors may affect environmental (hence genotypic) complexity, such as spatial structure, temporal fluctuations, or competitive co-evolution.

More is more: Today's typical numbers of generations, sizes of populations, and components inside individuals are still too small. Just like physics needs higher-energy accelerators and farther-reaching telescopes to understand matter and space-time, evolutionary computation needs a boost in computational power to understand the generation of complex functionality. Biological evolution involved 4 billion years and untold numbers of organisms. Nature could afford to be "wasteful", but we cannot. We expect that datacenter-scale computing power will be applied in the future to produce artificially evolved artifacts of great complexity. How will we apply such resources most efficiently to "scale up" to high complexity?

How should we measure evolved complexity?: The GDS track has recently added a new focus: defining quantitative metrics of evolved complexity. (Which is more complex - a mouse, or a stegosaurus?) The evolutionary computing community is badly in need of such metrics, which may be theoretical (e.g., Kolmogorov complexity) or more practical. Ideally, such metrics will be applicable across multiple problem domains and genetic architectures; however, any efforts will be welcomed. We encourage authors to submit papers on these quantitative metrics, which will be given special attention by the track chairs this year.

The GDS track invites all papers addressing open-ended evolution, including, but not limited to, the areas of:

* artificial development, artificial embryogeny
* evo-devo robotics, morphogenetic robotics
* evolution of evolvability
* gene regulatory networks
* grammar-based systems, generative systems, rewriting systems
* indirect mappings, compact encodings, novel representations
* morphogenetic engineering
* neural development, neuroevolution, augmenting topologies
* synthetic biology, artificial chemistry
* spatial computing, amorphous computing
* competitive co-evolution (arms races)
* complex, spatially structured, and dynamically changing environments
* diversity preservation, novelty search
* efficiently "scaling up" to large numbers of generations, individuals, and internal components
* measures of evolved complexity (theoretical, or practical)

VENUE
-----------

The track and conference will be held in Vancouver, BC, Canada.

IMPORTANT DATES
---------------------------

Abstract submission: January 15, 2014 (required, new for 2014!)
Submission of full papers: January 29, 2014 (NO extensions this year)
Notification of paper acceptance: March 12, 2014
Camera ready submission: April 14, 2014
Advance registration: May 2, 2014
Conference: July 12-16, 2014 in Vancouver, BC, Canada


FOR MORE INFORMATION:
-----------------------------------------

Please see the GDS 2014 website (http://www.mepalmer.net/gds2014) or you can join the GDS Google Group (https://groups.google.com/forum/#!forum/gds-gecco) to see the latest updates.

We look forward to reading your paper.

- Sebastian Risi and Michael Palmer, GDS track chairs

Related Resources

GECCO 2024   Genetic and Evolutionary Computation Conference
ECAI 2024   27th European Conference on Artificial Intelligence
GECCO 2024   The Genetic and Evolutionary Computation Conference (GECCO 2024)
IEEE ICA 2022   The 6th IEEE International Conference on Agents
PCDS 2024   The 1st International Symposium on Parallel Computing and Distributed Systems
NeurIPS 2024   The Thirty-Eighth Annual Conference on Neural Information Processing Systems
AI&S 2024   Call For Papers: Special issue of the Journal AI & Society - The Impact of Generative AI on Human Creativity
CCVPR 2024   2024 International Joint Conference on Computer Vision and Pattern Recognition (CCVPR 2024)
IEEE-JBHI (SI) 2024   Special Issue on Revolutionizing Healthcare Informatics with Generative AI: Innovations and Implications
AIM@EPIA 2024   Artificial Intelligence in Medicine