• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 20 matches

• 2020
• 
  Wolfgang Banzhaf, Erik D. Goodman, Leigh Sheneman, Leonardo Trujillo, Bill Worzel:
  Genetic Programming Theory and Practice XVII [GPTP 2019, Michigan State University, East Lansing, Michigan, USA, May 16-19, 2019]. Springer 2020, ISBN 978-3-030-39957-3 [contents]
• 2019
• 
  Robert J. Smith, Malcolm I. Heywood:
  Evolving a Dota 2 Hero Bot with a Probabilistic Shared Memory Model. GPTP 2019: 345-366
• 
  Austin J. Ferguson, Jose Guadalupe Hernandez, Daniel Junghans, Alexander Lalejini, Emily L. Dolson, Charles Ofria:
  Characterizing the Effects of Random Subsampling on Lexicase Selection. GPTP 2019: 1-23
• 
  Ivo Gonçalves, Marta Seca, Mauro Castelli:
  Explorations of the Semantic Learning Machine Neuroevolution Algorithm: Dynamic Training Data Use, Ensemble Construction Methods, and Deep Learning Perspectives. GPTP 2019: 39-62
• 
  Ting Hu:
  Can Genetic Programming Perform Explainable Machine Learning for Bioinformatics? GPTP 2019: 63-77
• 
  Lukas Kammerer, Gabriel Kronberger, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller:
  Symbolic Regression by Exhaustive Search: Reducing the Search Space Using Syntactical Constraints and Efficient Semantic Structure Deduplication. GPTP 2019: 79-99
• 
  Stephen Kelly, Wolfgang Banzhaf:
  Temporal Memory Sharing in Visual Reinforcement Learning. GPTP 2019: 101-119
• 
  Douglas Kirkpatrick, Arend Hintze:
  The Evolution of Representations in Genetic Programming Trees. GPTP 2019: 121-143
• 
  Arthur K. Kordon, Theresa Kotanchek, Mark E. Kotanchek:
  How Competitive Is Genetic Programming in Business Data Science Applications? GPTP 2019: 145-163
• 
  Joel Lehman:
  Evolutionary Computation and AI Safety - Research Problems Impeding Routine and Safe Real-World Application of Evolution. GPTP 2019: 181-200
• 
  Miguel Nicolau, James McDermott:
  Genetic Programming Symbolic Regression: What Is the Prior on the Prediction? GPTP 2019: 201-225
• 
  Francisco Fernández de Vega, Gustavo Olague, Francisco Chávez de la O, Daniel Lanza, Wolfgang Banzhaf, Erik D. Goodman:
  It Is Time for New Perspectives on How to Fight Bloat in GP. GPTP 2019: 25-38
• 
  Gustavo Olague, Mariana Chan-Ley:
  Hands-on Artificial Evolution Through Brain Programming. GPTP 2019: 227-253
• 
  Edward R. Pantridge, Thomas Helmuth, Lee Spector:
  Comparison of Linear Genome Representations for Software Synthesis. GPTP 2019: 255-274
• 
  Anil Kumar Saini, Lee Spector:
  Using Modularity Metrics as Design Features to Guide Evolution in Genetic Programming. GPTP 2019: 165-180
• 
  Hormoz Shahrzad, Babak Hodjat, Camille Dollé, Andrei Denissov, Simon Lau, Donn Goodhew, Justin Dyer, Risto Miikkulainen:
  Enhanced Optimization with Composite Objectives and Novelty Pulsation. GPTP 2019: 275-293
• 
  Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz:
  New Pathways in Coevolutionary Computation. GPTP 2019: 295-305
• 
  Andrew N. Sloss, Steven Gustafson:
  2019 Evolutionary Algorithms Review. GPTP 2019: 307-344
• 
  David Robert White, Benjamin Fowler, Wolfgang Banzhaf, Earl T. Barr:
  Modelling Genetic Programming as a Simple Sampling Algorithm. GPTP 2019: 367-381
• 
  Yuan Yuan, Wolfgang Banzhaf:
  An Evolutionary System for Better Automatic Software Repair. GPTP 2019: 383-406