Semantic Methods in Genetic Programming (SMGP)
Workshop at Parallel Problem Solving from Nature 2014 conference
Ljubljana, Slovenia, 13 September 2014
Quick links
- Call for papers (the list of submissions is already closed)
- NEW! List of accepted papers
- NEW! Workshop schedule
Call for Papers
Genetic programming (GP)—the application of evolutionary computing techniques to the creation of computer programs—has been a key topic in computational intelligence in the last couple of decades. In the last few years a rising topic in GP has been the use of semantic methods. The aim of this is to provide a way of exploring the input-output behaviour of programs, which is ultimately what matters for problem solving. This contrasts with much previous work in GP, where operators transform the program code and the effect on program behaviour is indirect. This new approach has produced substantially better results on a number of problems, both benchmark problems and real-world applications in areas such as pharmacy; and, has been grounded in a body of theory, which also informs algorithm design.
The main goal of the workshop is to foster discussions rather than present finished work. In tradition with the PPSN workshops, the extended abstracts are not published in the conference proceedings. However, the organisers will make both abstracts and slides available online on the workshop webpage. The workshop is associated with a Special Issue of Genetic Programming and Evolvable Machines Journal by Springer, and provides an opportunity to have an open discussion and receive feedback in preparation for submission to that special issue.
The workshop will take place at PPSN 2014 on September 13, 2014, and researchers working in GP and other branches of evolutionary computation are strongly encouraged to participate.
Scope
All aspects of research related to semantic aspects in GP will be considered, including:
- analysis and design of GP algorithms involving phenotypes/behaviours of programs,
- design of problem-specific semantic-aware representations and operators,
- the use of formal semantic-related methods in GP.
Dates
Submission Deadline: 31 May 2014- PPSN Conference: 13-17 September 2014
- SMGP date: 13 September 2014
Other details
Workshop organizers
- Colin Johnson, School of Computing, University of Kent, UK
- Krzysztof Krawiec, Institute of Computing Science, Poznan University of Technology, Poland
- Alberto Moraglio, College of Engineering, Mathematics and Physical Sciences, University of Exeter, UK
- Michael O’Neill, UCD Complex & Adaptive Systems Laboratory, School of Computer Science & Informatics, University College Dublin, Ireland
List of accepted presentations (with links to extended abstracts)
A Study of Semantic Geometric Crossover Operators in Regression Problems by Julio Albinati, Gisele L. Pappa, Fernando E. B. Otero, Luiz Ot'avio V. B. Oliveira
The Influence of Population Size on Geometric Semantic GP by Mauro Castelli, Luca Manzoni, Sara Silva, Leonardo Vanneschi
Self-tuning Geometric Semantic GP by Mauro Castelli, Luca Manzoni, Sara Silva, Leonardo Vanneschi
Semantic Operators for Evolutionary Art by Joao Correia, Penousal Machado
Information Theory, Fitness, and Sampling Semantics by Colin G. Johnson, John R. Woodward
Asymptotic Genetic Improvement Programming via Type Functors and Catamorphisms by Zoltan A. Kocsis, Jerry Swan
A framework for measuring the generalization ability of Geometric Semantic Genetic Programming (GSGP) for Black-Box Boolean Functions Learning by Andrea Mambrini, Yang Yu, Xin Yao
Geometric Semantic Grammatical Evolution by Alberto Moraglio, James McDermott, Michael O'Neill
An Efficient Implementation of GSGP using Higher-Order Functions and Memoization by Alberto Moraglio
Guarantees of Progress for Geometric SemanticGenetic Programming by Tomasz P. Pawlak, Krzysztof Krawiec
Semantically-meaningful Numeric Constants for Genetic Programming by Jerry Swan, John Drake, Krzysztof Krawiec
Analysis of Semantic Building Blocks via Groebner Bases by Jerry Swan, Geoffrey K. Neumann, Krzysztof Krawiec
Workshop schedule
SMGP will be a full-day, four-session workshop on September 13, 2014
For every talk, 15 minutes are allocated, plus 10 minutes for questions and discussion.
Session 1 (Chair: Alberto Moraglio)
- 9:00-9:05 Introduction
- 9:05-9:30 Semantically-meaningful Numeric Constants for Genetic Programming by Jerry Swan, John Drake, Krzysztof Krawiec
- 9:30-9:55 Information Theory, Fitness, and Sampling Semantics by Colin G. Johnson, John R. Woodward
- 9:55-10:20 Asymptotic Genetic Improvement Programming via Type Functors and Catamorphisms by Zoltan A. Kocsis, Jerry Swan
10:30-11:00 Coffee Break
Session 2 (Chair: Colin Johnson)
- 11:00-11:15 Introduction to Geometric Semantic Genetic Programming, Alberto Moraglio
- 11:15-11:40 Semantic Operators for Evolutionary Art by Joao Correia, Penousal Machado
- 11:40-12:05 A Framework for Measuring the Generalization Ability of Geometric Semantic Genetic Programming (GSGP) for Black-Box Boolean Functions Learning by Andrea Mambrini, Yang Yu, Xin Yao
- 12:05-12:30 Guarantees of Progress for Geometric Semantic Genetic Programming by Tomasz P. Pawlak, Krzysztof Krawiec
12:30-14:00 Lunch break
Session 3 (Chair: Michael O’Neill Penousal Machado)
- 14:00-14:25 Analysis of Semantic Building Blocks via Groebner Bases by Jerry Swan, Geoffrey K. Neumann, Krzysztof Krawiec
- 14:25-14:50 An Efficient Implementation of GSGP using Higher-Order Functions and Memoization by Alberto Moraglio
- 14:50-15:15 The Influence of Population Size on Geometric Semantic GP by Mauro Castelli, Luca Manzoni, Sara Silva, Leonardo Vanneschi
15:30-16:00 Coffee Break
Session 4 (Chair: Krzysztof Krawiec)
- 16:00-16:25 A Study of Semantic Geometric Crossover Operators in Regression Problems by Julio Albinati, Gisele L. Pappa, Fernando E. B. Otero, Luiz Otávio V. B. Oliveira
- 16:25-16:50 Self-tuning Geometric Semantic GP by Mauro Castelli, Luca Manzoni, Sara Silva, Leonardo Vanneschi
- 16:50-17:15 Geometric Semantic Grammatical Evolution by Alberto Moraglio, James McDermott, Michael O'Neill
- 17:15-17:30 Closing Discussion