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ORCIDWolfgang Banzhaf
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- affiliation: Michigan State University, East Lansing, MI, USA
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2020 – today
- 2024
[j84]Iliya Miralavy, Wolfgang Banzhaf:
A Spatial Artificial Chemistry Implementation of a Gene Regulatory Network Aimed at Generating Protein Concentration Dynamics. Artif. Life 30(1): 65-90 (2024)- [j83]Hengzhe Zhang, Qi Chen
, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang:
A geometric semantic macro-crossover operator for evolutionary feature construction in regression. Genet. Program. Evolvable Mach. 25(1): 2 (2024) - [j82]Zhixing Huang, Yi Mei, Fangfang Zhang, Mengjie Zhang, Wolfgang Banzhaf:
Bridging directed acyclic graphs to linear representations in linear genetic programming: a case study of dynamic scheduling. Genet. Program. Evolvable Mach. 25(1): 5 (2024) - [j81]Wolfgang Banzhaf:
"The physics of evolution" by Michael W. Roth, Crc press, 2023. Genet. Program. Evolvable Mach. 25(2): 16 (2024) - [j80]Nicolas Scalzitti, Iliya Miralavy, David E. Korenchan, Christian T. Farrar, Assaf A. Gilad, Wolfgang Banzhaf:
Computational peptide discovery with a genetic programming approach. J. Comput. Aided Mol. Des. 38(1): 17 (2024) - [j79]Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang:
Modular Multitree Genetic Programming for Evolutionary Feature Construction for Regression. IEEE Trans. Evol. Comput. 28(5): 1455-1469 (2024) - [j78]Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang:
A Semantic-Based Hoist Mutation Operator for Evolutionary Feature Construction in Regression. IEEE Trans. Evol. Comput. 28(6): 1689-1703 (2024) - [c164]Yuri Lavinas, Nathan Haut, William Punch, Wolfgang Banzhaf, Sylvain Cussat-Blanc:
Data Sampling via Active Learning in Cartesian Genetic Programming for Biomedical Data. CEC 2024: 1-8 - [c163]Salman Ali, Cedric Gondro, Qiben Yan, Wolfgang Banzhaf:
End-to-End Decentralized Tracking of Carbon Footprint using Internet of Things and Distributed Databases. CIoT 2024: 1-8 - [c162]Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang:
Improving Generalization of Evolutionary Feature Construction with Minimal Complexity Knee Points in Regression. EuroGP 2024: 142-158 - [c161]Yuri Lavinas, Nathaniel Haut, William Punch, Wolfgang Banzhaf, Sylvain Cussat-Blanc:
Dynamically Sampling biomedical Images For Genetic Programming. GECCO Companion 2024: 515-518 - [c160]Wolfgang Banzhaf, Ting Hu:
Linear Genetic Programming. GECCO Companion 2024: 759-771 - [c159]Wolfgang Banzhaf, Illya Bakurov:
On the Nature of the Phenotype in Tree Genetic Programming. GECCO 2024 - [c158]Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang:
A Semantic-based Hoist Mutation Operator for Evolutionary Feature Construction in Regression [Hot off the Press]. GECCO Companion 2024: 65-66 - [c157]Sardar Bin Murtaza, Aidan Mccoy, Zhiyuan Ren, Aidan Murphy, Wolfgang Banzhaf:
LLM Fault Localisation within Evolutionary Computation Based Automated Program Repair. GECCO Companion 2024: 1824-1829 - [c156]Vinícius Veloso de Melo, Wolfgang Banzhaf, Giovanni Iacca:
Accelerating GP Genome Evaluation Through Real Compilation with a Multiple Program Single Data Approach. GECCO Companion 2024: 2041-2049 - [c155]Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang:
Bias-Variance Decomposition: An Effective Tool to Improve Generalization of Genetic Programming-based Evolutionary Feature Construction for Regression. GECCO 2024 - [c154]Salman Ali, Cedric Gondro, Qiben Yan, Wolfgang Banzhaf:
A Distributed System for Optimization of Carbon Emitting Resource Consumption in Supply Chains. ISNCC 2024: 1-8 - [c153]Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang:
P-Mixup: Improving Generalization Performance of Evolutionary Feature Construction with Pessimistic Vicinal Risk Minimization. PPSN (1) 2024: 201-220 - [c152]Yuri Lavinas, Nathan Haut, William Punch, Wolfgang Banzhaf, Sylvain Cussat-Blanc:
Adaptive Sampling of Biomedical Images with Cartesian Genetic Programming. PPSN (1) 2024: 256-272 - [c151]Christopher Crary, Bogdan Burlacu, Wolfgang Banzhaf:
Enhancing the Computational Efficiency of Genetic Programming Through Alternative Floating-Point Primitives. PPSN (1) 2024: 322-339 - [i31]Wolfgang Banzhaf, Illya Bakurov:
On The Nature Of The Phenotype In Tree Genetic Programming. CoRR abs/2402.08011 (2024) - [i30]Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang:
Sharpness-Aware Minimization for Evolutionary Feature Construction in Regression. CoRR abs/2405.06869 (2024) - [i29]Illya Bakurov, Nathan Haut, Wolfgang Banzhaf:
Sharpness-Aware Minimization in Genetic Programming. CoRR abs/2405.10267 (2024) - [i28]Zhixing Huang, Yi Mei, Fangfang Zhang, Mengjie Zhang, Wolfgang Banzhaf:
Multi-Representation Genetic Programming: A Case Study on Tree-based and Linear Representations. CoRR abs/2405.14268 (2024) - 2023
- [j77]Yuan Yuan, Wolfgang Banzhaf:
Iterative genetic improvement: Scaling stochastic program synthesis. Artif. Intell. 322: 103962 (2023) - [j76]Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang:
MAP-Elites for Genetic Programming-Based Ensemble Learning: An Interactive Approach [AI-eXplained]. IEEE Comput. Intell. Mag. 18(4): 62-63 (2023) - [c150]Ting Hu, Gabriela Ochoa, Wolfgang Banzhaf:
Phenotype Search Trajectory Networks for Linear Genetic Programming. EuroGP 2023: 52-67 - [c149]Hengzhe Zhang, Qi Chen, Alberto Tonda, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang:
MAP-Elites with Cosine-Similarity for Evolutionary Ensemble Learning. EuroGP 2023: 84-100 - [c148]Iliya Miralavy, Wolfgang Banzhaf:
Spatial Genetic Programming. EuroGP 2023: 260-275 - [c147]Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang:
Relieving Genetic Programming from Coefficient Learning for Symbolic Regression via Correlation and Linear Scaling. GECCO 2023: 420-428 - [c146]Ritam Guha, Wei Ao, Stephen Kelly, Vishnu Boddeti, Erik D. Goodman, Wolfgang Banzhaf, Kalyanmoy Deb:
MOAZ: A Multi-Objective AutoML-Zero Framework. GECCO 2023: 485-492 - [c145]Nathan Haut, Bill Punch, Wolfgang Banzhaf:
Active Learning Informs Symbolic Regression Model Development in Genetic Programming. GECCO Companion 2023: 587-590 - [c144]Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang:
A Double Lexicase Selection Operator for Bloat Control in Evolutionary Feature Construction for Regression. GECCO 2023: 1194-1202 - [c143]Nathan Haut, Wolfgang Banzhaf, Bill Punch, Dirk Colbry:
Accelerating Image Analysis Research with Active Learning Techniques in Genetic Programming. GPTP 2023: 45-64 - [c142]Wolfgang Banzhaf, Ting Hu, Gabriela Ochoa:
How the Combinatorics of Neutral Spaces Leads Genetic Programming to Discover Simple Solutions. GPTP 2023: 65-86 - [c141]Stephen Kelly, Daniel S. Park, Xingyou Song, Mitchell McIntire, Pranav Nashikkar, Ritam Guha, Wolfgang Banzhaf, Kalyanmoy Deb, Vishnu Naresh Boddeti, Jie Tan, Esteban Real:
Discovering Adaptable Symbolic Algorithms from Scratch. IROS 2023: 3889-3896 - [c140]Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang:
Automatically Choosing Selection Operator Based on Semantic Information in Evolutionary Feature Construction. PRICAI (2) 2023: 385-397 - [e13]Leonardo Trujillo, Stephan M. Winkler, Sara Silva, Wolfgang Banzhaf:
Genetic Programming Theory and Practice XIX [GPTP 2022]. Springer 2023, ISBN 978-981-19-8459-4 [contents] - [i27]Stephen Kelly, Daniel S. Park, Xingyou Song, Mitchell McIntire, Pranav Nashikkar, Ritam Guha, Wolfgang Banzhaf, Kalyanmoy Deb, Vishnu Naresh Boddeti, Jie Tan, Esteban Real:
Discovering Adaptable Symbolic Algorithms from Scratch. CoRR abs/2307.16890 (2023) - [i26]Nathan Haut, Wolfgang Banzhaf, Bill Punch:
Active Learning in Genetic Programming: Guiding Efficient Data Collection for Symbolic Regression. CoRR abs/2308.00672 (2023) - 2022
- [j75]Gustavo Recio, Wolfgang Banzhaf, Roger White:
From Dynamics to Novelty: An Agent-Based Model of the Economic System. Artif. Life 28(1): 58-95 (2022) - [j74]William B. Langdon, Wolfgang Banzhaf:
Long-Term Evolution Experiment with Genetic Programming. Artif. Life 28(2): 173-204 (2022) - [j73]Akbar Telikani, Amirhessam Tahmassebi, Wolfgang Banzhaf, Amir H. Gandomi:
Evolutionary Machine Learning: A Survey. ACM Comput. Surv. 54(8): 161:1-161:35 (2022) - [j72]Yuan Yuan, Wolfgang Banzhaf:
Expensive Multiobjective Evolutionary Optimization Assisted by Dominance Prediction. IEEE Trans. Evol. Comput. 26(1): 159-173 (2022) - [c139]William B. Langdon, Wolfgang Banzhaf:
Long-term evolution experiment with genetic programming [hot of the press]. GECCO Companion 2022: 29-30 - [c138]Nathan Haut, Wolfgang Banzhaf, Bill Punch:
Active learning improves performance on symbolic regression tasks in StackGP. GECCO Companion 2022: 550-553 - [c137]Hannah Peeler, Shuyue Stella Li, Andrew N. Sloss, Kenneth N. Reid, Yuan Yuan, Wolfgang Banzhaf:
Optimizing LLVM pass sequences with shackleton: a linear genetic programming framework. GECCO Companion 2022: 578-581 - [c136]Shuyue Stella Li, Hannah Peeler, Andrew N. Sloss, Kenneth N. Reid, Wolfgang Banzhaf:
Genetic improvement in the shackleton framework for optimizing LLVM pass sequences. GECCO Companion 2022: 1938-1939 - [c135]Nathan Haut, Wolfgang Banzhaf, Bill Punch:
Correlation Versus RMSE Loss Functions in Symbolic Regression Tasks. GPTP 2022: 31-55 - [e12]Wolfgang Banzhaf, Leonardo Trujillo, Stephan Winkler, Bill Worzel:
Genetic Programming Theory and Practice XVIII [GPTP 2021]. Springer 2022, ISBN 978-981-16-8112-7 [contents] - [i25]Hannah Peeler, Shuyue Stella Li, Andrew N. Sloss, Kenneth N. Reid, Yuan Yuan, Wolfgang Banzhaf:
Optimizing LLVM Pass Sequences with Shackleton: A Linear Genetic Programming Framework. CoRR abs/2201.13305 (2022) - [i24]Iliya Miralavy, Alexander Bricco, Assaf A. Gilad, Wolfgang Banzhaf:
Using Genetic Programming to Predict and Optimize Protein Function. CoRR abs/2202.04039 (2022) - [i23]Nathan Haut, Wolfgang Banzhaf, Bill Punch:
Active Learning Improves Performance on Symbolic RegressionTasks in StackGP. CoRR abs/2202.04708 (2022) - [i22]Yuan Yuan, Wolfgang Banzhaf:
Iterative Genetic Improvement: Scaling Stochastic Program Synthesis. CoRR abs/2202.13040 (2022) - [i21]Shuyue Stella Li, Hannah Peeler, Andrew N. Sloss, Kenneth N. Reid, Wolfgang Banzhaf:
Genetic Improvement in the Shackleton Framework for Optimizing LLVM Pass Sequences. CoRR abs/2204.13261 (2022) - [i20]Nathan Haut, Wolfgang Banzhaf, Bill Punch:
Correlation versus RMSE Loss Functions in Symbolic Regression Tasks. CoRR abs/2205.15990 (2022) - [i19]Iliya Miralavy, Wolfgang Banzhaf:
An Artificial Chemistry Implementation of a Gene Regulatory Network. CoRR abs/2209.04114 (2022) - [i18]Ting Hu, Gabriela Ochoa, Wolfgang Banzhaf:
Phenotype Search Trajectory Networks for Linear Genetic Programming. CoRR abs/2211.08516 (2022) - 2021
- [j71]Stephen Kelly, Tatiana Voegerl, Wolfgang Banzhaf, Cedric Gondro:
Evolving hierarchical memory-prediction machines in multi-task reinforcement learning. Genet. Program. Evolvable Mach. 22(4): 573-605 (2021) - [j70]Zhichao Lu, Gautam Sreekumar, Erik D. Goodman, Wolfgang Banzhaf, Kalyanmoy Deb, Vishnu Naresh Boddeti:
Neural Architecture Transfer. IEEE Trans. Pattern Anal. Mach. Intell. 43(9): 2971-2989 (2021) - [j69]Zhichao Lu, Ian Whalen, Yashesh D. Dhebar, Kalyanmoy Deb, Erik D. Goodman, Wolfgang Banzhaf, Vishnu Naresh Boddeti:
Multiobjective Evolutionary Design of Deep Convolutional Neural Networks for Image Classification. IEEE Trans. Evol. Comput. 25(2): 277-291 (2021) - [j68]Stephen Kelly, Robert J. Smith, Malcolm I. Heywood, Wolfgang Banzhaf:
Emergent Tangled Program Graphs in Partially Observable Recursive Forecasting and ViZDoom Navigation Tasks. ACM Trans. Evol. Learn. Optim. 1(3): 11:1-11:41 (2021) - [c134]Kenneth N. Reid, Iliya Miralavy, Stephen Kelly, Wolfgang Banzhaf, Cedric Gondro:
The factory must grow: automation in Factorio. GECCO Companion 2021: 243-244 - [i17]Kenneth N. Reid, Iliya Miralavy, Stephen Kelly, Wolfgang Banzhaf, Cedric Gondro:
The Factory Must Grow: Automation in Factorio. CoRR abs/2102.04871 (2021) - [i16]Stephen Kelly, Tatiana Voegerl, Wolfgang Banzhaf, Cedric Gondro:
Evolving Hierarchical Memory-Prediction Machines in Multi-Task Reinforcement Learning. CoRR abs/2106.12659 (2021) - 2020
- [j67]Francisco Fernández de Vega, Gustavo Olague, Daniel Lanza, Francisco Chávez de la O, Wolfgang Banzhaf, Erik D. Goodman, Jose Menendez-Clavijo, Axel Martinez:
Time and Individual Duration in Genetic Programming. IEEE Access 8: 38692-38713 (2020) - [j66]Ting Hu, Marco Tomassini, Wolfgang Banzhaf:
A network perspective on genotype-phenotype mapping in genetic programming. Genet. Program. Evolvable Mach. 21(3): 375-397 (2020) - [j65]Yuan Yuan, Wolfgang Banzhaf:
Toward Better Evolutionary Program Repair: An Integrated Approach. ACM Trans. Softw. Eng. Methodol. 29(1): 5:1-5:53 (2020) - [j64]Yuan Yuan, Wolfgang Banzhaf:
ARJA: Automated Repair of Java Programs via Multi-Objective Genetic Programming. IEEE Trans. Software Eng. 46(10): 1040-1067 (2020) - [c133]Zhichao Lu, Kalyanmoy Deb, Erik D. Goodman, Wolfgang Banzhaf, Vishnu Naresh Boddeti:
NSGANetV2: Evolutionary Multi-objective Surrogate-Assisted Neural Architecture Search. ECCV (1) 2020: 35-51 - [c132]Stephen Kelly, Jacob Newsted, Wolfgang Banzhaf, Cedric Gondro:
A modular memory framework for time series prediction. GECCO 2020: 949-957 - [c131]Zhichao Lu, Ian Whalen, Yashesh D. Dhebar, Kalyanmoy Deb, Erik D. Goodman, Wolfgang Banzhaf, Vishnu Naresh Boddeti:
NSGA-Net: Neural Architecture Search using Multi-Objective Genetic Algorithm (Extended Abstract). IJCAI 2020: 4750-4754 - [c130]Gustavo Recio, Wolfgang Banzhaf, Roger White:
A Study of Severe Disruption in an Artificial Economy. ALIFE 2020: 180-187 - [e11]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] - [i15]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. CoRR abs/2005.00603 (2020) - [i14]Zhichao Lu, Gautam Sreekumar, Erik D. Goodman, Wolfgang Banzhaf, Kalyanmoy Deb, Vishnu Naresh Boddeti:
Neural Architecture Transfer. CoRR abs/2005.05859 (2020) - [i13]Wolfgang Banzhaf:
The Effects of Taxes on Wealth Inequality in Artificial Chemistry Models of Economic Activity. CoRR abs/2007.02934 (2020) - [i12]Zhichao Lu, Kalyanmoy Deb, Erik D. Goodman, Wolfgang Banzhaf, Vishnu Naresh Boddeti:
NSGANetV2: Evolutionary Multi-Objective Surrogate-Assisted Neural Architecture Search. CoRR abs/2007.10396 (2020)
2010 – 2019
- 2019
- [c129]Ting Hu, Marco Tomassini, Wolfgang Banzhaf:
Complex Network Analysis of a Genetic Programming Phenotype Network. EuroGP 2019: 49-63 - [c128]Hamed Bolandi, Wolfgang Banzhaf, Nizar Lajnef, Kaveh Barri, Amir Hossein Alavi:
Bond strength prediction of FRP-bar reinforced concrete: a multi-gene genetic programming approach. GECCO (Companion) 2019: 364 - [c127]Zhichao Lu, Ian Whalen, Vishnu Boddeti, Yashesh D. Dhebar, Kalyanmoy Deb, Erik D. Goodman, Wolfgang Banzhaf:
NSGA-Net: neural architecture search using multi-objective genetic algorithm. GECCO 2019: 419-427 - [c126]Vinícius Veloso de Melo, Danilo Vasconcellos Vargas, Wolfgang Banzhaf:
Batch tournament selection for genetic programming: the quality of lexicase, the speed of tournament. GECCO 2019: 994-1002 - [c125]Yuan Yuan, Wolfgang Banzhaf:
A hybrid evolutionary system for automatic software repair. GECCO 2019: 1417-1425 - [c124]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 - [c123]Stephen Kelly, Wolfgang Banzhaf:
Temporal Memory Sharing in Visual Reinforcement Learning. GPTP 2019: 101-119 - [c122]David Robert White, Benjamin Fowler, Wolfgang Banzhaf, Earl T. Barr:
Modelling Genetic Programming as a Simple Sampling Algorithm. GPTP 2019: 367-381 - [c121]Yuan Yuan, Wolfgang Banzhaf:
An Evolutionary System for Better Automatic Software Repair. GPTP 2019: 383-406 - [c120]William B. Langdon, Wolfgang Banzhaf:
Continuous Long-Term Evolution of Genetic Programming. ALIFE 2019: 388-395 - [e10]Wolfgang Banzhaf, Lee Spector, Leigh Sheneman:
Genetic Programming Theory and Practice XVI, [GPTP 2018, University of Michigan, Ann Arbor, USA, May 17-20, 2018]. Genetic and Evolutionary Computation, Springer 2019, ISBN 978-3-030-04734-4 [contents] - [i11]Roger White, Wolfgang Banzhaf:
Putting Natural Time into Science. CoRR abs/1901.07357 (2019) - [i10]William B. Langdon, Wolfgang Banzhaf:
Faster Genetic Programming GPquick via multicore and Advanced Vector Extensions. CoRR abs/1902.09215 (2019) - [i9]Vinícius Veloso de Melo, Danilo Vasconcellos Vargas, Wolfgang Banzhaf:
Batch Tournament Selection for Genetic Programming. CoRR abs/1904.08658 (2019) - [i8]Zhichao Lu, Ian Whalen, Yashesh D. Dhebar, Kalyanmoy Deb, Erik D. Goodman, Wolfgang Banzhaf, Vishnu Naresh Boddeti:
Multi-Criterion Evolutionary Design of Deep Convolutional Neural Networks. CoRR abs/1912.01369 (2019) - 2018
- [j63]Sylvain Cussat-Blanc, Kyle Ira Harrington, Wolfgang Banzhaf:
Artificial Gene Regulatory Networks - A Review. Artif. Life 24(4) (2018) - [j62]Vinícius Veloso de Melo, Wolfgang Banzhaf:
Automatic feature engineering for regression models with machine learning: An evolutionary computation and statistics hybrid. Inf. Sci. 430: 287-313 (2018) - [j61]Vinícius Veloso de Melo, Wolfgang Banzhaf:
Drone Squadron Optimization: a novel self-adaptive algorithm for global numerical optimization. Neural Comput. Appl. 30(10): 3117-3144 (2018) - [c119]Matthew Andres Moreno, Wolfgang Banzhaf, Charles Ofria:
Learning an evolvable genotype-phenotype mapping. GECCO 2018: 983-990 - [c118]Honglin Bao, Qiqige Wuyun, Wolfgang Banzhaf:
Evolution of Cooperation through Genetic Collective Learning and Imitation in Multiagent Societies. ALIFE 2018: 436-443 - [e9]Wolfgang Banzhaf, Randal S. Olson, William A. Tozier, Rick L. Riolo:
Genetic Programming Theory and Practice XV, [GPTP 2017, University of Michigan, Ann Arbor, USA, May 18-20, 2017]. Genetic and Evolutionary Computation, Springer 2018, ISBN 978-3-319-90511-2 [contents] - [i7]Zhichao Lu, Ian Whalen, Vishnu Boddeti, Yashesh D. Dhebar, Kalyanmoy Deb, Erik D. Goodman, Wolfgang Banzhaf:
NSGA-NET: A Multi-Objective Genetic Algorithm for Neural Architecture Search. CoRR abs/1810.03522 (2018) - [i6]Emily L. Dolson, Wolfgang Banzhaf, Charles Ofria:
Ecological theory provides insights about evolutionary computation. PeerJ Prepr. 6: e27315 (2018) - 2017
- [j60]Vinícius Veloso de Melo, Wolfgang Banzhaf:
Improving the prediction of material properties of concrete using Kaizen Programming with Simulated Annealing. Neurocomputing 246: 25-44 (2017) - [c117]Sylvain Cussat-Blanc, Wolfgang Banzhaf:
Introduction to gene regulatory networks. GECCO (Companion) 2017: 359-372 - [c116]Amir Tavafi, Wolfgang Banzhaf:
A hybrid genetic programming decision making system for RoboCup soccer simulation. GECCO 2017: 1025-1032 - [c115]Emily L. Dolson, Wolfgang Banzhaf, Charles Ofria:
Applying Ecological Principles to Genetic Programming. GPTP 2017: 73-88 - [c114]Esteban Ricalde, Wolfgang Banzhaf:
Evolving Adaptive Traffic Signal Controllers for a Real Scenario Using Genetic Programming with an Epigenetic Mechanism. ICMLA 2017: 897-902 - [i5]Vinícius Veloso de Melo, Wolfgang Banzhaf:
Drone Squadron Optimization: a Self-adaptive Algorithm for Global Numerical Optimization. CoRR abs/1703.04561 (2017) - [i4]Yuan Yuan, Wolfgang Banzhaf:
ARJA: Automated Repair of Java Programs via Multi-Objective Genetic Programming. CoRR abs/1712.07804 (2017) - 2016
- [j59]Tim Taylor, Mark A. Bedau, Alastair Channon, David H. Ackley, Wolfgang Banzhaf, Guillaume Beslon, Emily L. Dolson, Tom Froese, Simon J. Hickinbotham, Takashi Ikegami, Barry McMullin, Norman H. Packard, Steen Rasmussen, Nathaniel Virgo, Eran Agmon, Edward Clark, Simon McGregor, Charles Ofria, Glen E. P. Ropella, Lee Spector, Kenneth O. Stanley, Adam Stanton, Christopher Steven Timperley, Anya E. Vostinar, Michael J. Wiser:
Open-Ended Evolution: Perspectives from the OEE Workshop in York. Artif. Life 22(3): 408-423 (2016) - [j58]Wolfgang Banzhaf, Bert Baumgaertner, Guillaume Beslon, René Doursat, James A. Foster, Barry McMullin, Vinícius Veloso de Melo, Thomas Miconi, Lee Spector, Susan Stepney, Roger White:
Defining and simulating open-ended novelty: requirements, guidelines, and challenges. Theory Biosci. 135(3): 131-161 (2016) - [j57]Javad Rahimipour Anaraki, Saeed Samet, Wolfgang Banzhaf, Mahdi Eftekhari:
A New Fuzzy-Rough Hybrid Merit to Feature Selection. Trans. Rough Sets 20: 1-23 (2016) - [c113]