Magazine Interviews


Who's afraid of robots? Fake news in the age of AI. Daily Maverick (www.dailymaverick.co.za) , 5 March, 2019. [WWW].

Ctrl Alt Deliberate. Khuluma Magazine (Kululua.com) , pages 131-138, January, 2019. [PDF].

Is Data Science, Big Data, AI and Machine Learning blowing up in South Africa? Medium: Innovation Interviews (medium.com/qdivision), 13 March, 2018. [WWW].

Ethical Algorithms: How to Make Moral Machine Learning. Medium: Innovation Interviews (medium.com/qdivision), 16 January, 2018. [WWW].

Artificial Horizon. Fast Company South Africa (fastcompany.co.za) , pages 17-20, May, 2015. [PDF].


Books

Nitschke, G. (2009). Specialization in Collective Behavior Systems. Lambert Academic Publishing. Cologne, Germany.



Book Chapters

Goss, R., and Nitschke, G. (2014). Automating Network Protocol Identification. In Biju, I and Nauman I., editors, Case Studies in Intelligent Computing - Achievements and Trends, pages 109-123. Taylor and Francis, New York, USA. [PDF].

Nitschke, G., Schut, M., and Eiben, A. (2008). Emergent specialization in biologically inspired collective behavior systems. In Yang, A. and Shan, Y., editors, Intelligent Complex Adaptive Systems, pages 215-255. IGI Publishing. Hershey, USA. [PDF].

Journal Articles

Nitschke, G., and Didi, S. (2017). Evolutionary Policy Transfer and Search Methods for Boosting Behavior Quality: RoboCup Keep-Away Case Study. Frontiers in Robotics and AI . doi: 10.3389/frobt.2017.00062 [PDF].

Nitschke, G., Eiben, A., and Schut, M. (2012). Evolving Team Behaviors with Specialization. Genetic Programming and Evolvable Machines. 13(4): 493-536. [PDF].

Nitschke, G., Eiben, A., and Schut, M. (2011). Evolving Behavioral Specialization in Robot Teams to Solve a Collective Construction Task. Swarm and Evolutionary Computation. 2(1): 25-38. [PDF].

Nitschke, G., Schut, M., and Eiben, A. (2010). Collective Neuro-Evolution for Evolving Specialized Sensor Resolutions in a Multi-Rover Task. Evolutionary Intelligence. 3(1): 13-29. [PDF].

Nitschke, G. (2005). Designing emergent cooperation: A pursuit-evasion game case study. Artificial Life and Robotics, 9(4): 222-233. [PDF].

Nitschke, G. (2005). Emergence of cooperation: State of the art. Artificial Life, 11(3): 367-396. [PDF].

Nitschke, G. (2001). Cooperating Air Traffic Control Agents. Applied Artificial Intelligence, 15(2): 209-235.



Conference Proceedings

Nagar, D., Furman, A., and Nitschke. G. (2019). The Cost of Big Brains in Groups. In Proceedings of the 2019 Conference on Artificial Life (ALIFE 2019), pages 404-411, MIT Press, Newcastle, United Kingdom. [PDF].

Furman, A., Nagar, D., and Nitschke. G. (2019). The Cost of Morphological Complexity. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2019), pages 125-126, ACM Press, Prague, Czech Republic. [PDF].

Coetzee, L., and Nitschke. G. (2019). Evolving Optimal Sun-Shading Building Facades. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2019), pages 393-394, ACM Press, Prague, Czech Republic. [PDF].

Cohen, P., and Nitschke. G. (2019). Evolving Music with Emotional Feedback. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2019), pages 135-136, ACM Press, Prague, Czech Republic. [PDF].

Nagar, D., Furman, A., and Nitschke. G. (2019). The Cost of Complexity in Robot Bodies. In Proceedings of the IEEE Congress on Evolutionary Computation (IEEE CEC2019), pages 2713-2720, IEEE Press, Wellington, New Zealand. [PDF].

Putter, R., and Nitschke, G. (2018). Objective versus Non-Objective Search in Evolving Morphologically Robust Robot Controllers. In Proceedings of the IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2018), pages 2033-2040, IEEE Press, Bengaluru, India. [PDF].

Taylor, L., and Nitschke, G. (2018). Improving Deep Learning with Generic Data Augmentation. In Proceedings of the IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2018), pages 1542-1547, IEEE Press, Bengaluru, India. [PDF].

Shorten, D., and Nitschke, G. (2018). Exploring Exploration Catastrophes in Various Network Models. In Proceedings of the 2018 Conference on Artificial Life (ALIFE 2018), pages 374-381, MIT Press, Tokyo, Japan. [PDF].

Didi, S., and Nitschke, G. (2018). Policy Transfer Methods in RoboCup Keep-Away. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2018), pages 117-118, ACM Press, Kyoto, Japan. [PDF].

Witkowski, O., and Nitschke, G. (2018). The Dynamics of Cooperation versus Competition. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2018), pages 115-116, ACM Press, Kyoto, Japan. [PDF].

Putter, R., and Nitschke, G. (2018). Is Novelty Search Good for Evolving Morphologically Robust Robot Controllers? In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2018), pages 2051-2053, ACM, Stockholm, Sweden. [PDF].

Putter, R., and Nitschke, G. (2017). Evolving Morphological Robustness for Collective Robotics. In Proceedings of the IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2017), pages 1104-1111, IEEE Press, Honolulu, USA. [PDF].

Nitschke, J., Nitschke, G., Furman, A., and Cherry, M. (2017). Modeling Patterns of Wealth Disparity in Predynastic Upper Egypt. In Proceedings of the Fourteenth European Conference on the Synthesis and Simulation of Living Systems: Advances in Artificial Life (ECAL 2017), pages 322-323. MIT Press, Lyon, France. [PDF].

Parker, A., and Nitschke, G. (2017). Autonomous Intersection Driving with Neuro-Evolution. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2017), pages 133-134, ACM Press, Berlin, Germany. [PDF].

Goss, R., and Nitschke, G. (2017). Automated Pattern Identification and Classification: Anomaly Detection Case Study. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2017), pages 59-60, ACM Press, Berlin, Germany. [PDF].

Parker, A., and Nitschke, G. (2017). How to Best Automate Intersection Management. In Proceedings of the IEEE Congress on Evolutionary Computation (IEEE CEC 2017), pages 1247-1254, IEEE Press, San Sebastian, Spain. [PDF].

Huang, A., and Nitschke, G. (2017). Evolving Collective Driving Behaviors. In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2017), pages 1573-1574, ACM, Sao Paulo, Brazil. [PDF].

Shorten, D., and Nitschke, G. (2017). The Two Regimes of Neutral Evolution: Localization on Hubs and Delocalized Diffusion. In Proceedings of the European Conference on the Applications of Evolutionary Computation (Evostar 2017), pages 310-325, Springer, Amsterdam, the Netherlands. [PDF].

Shorten, D., and Nitschke, G. (2016). Neutral Network Assortativity Shapes Whether Selective Pressure Promotes or Hinders Robustness. In Proceedings of the IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2016), pages 2370-2376, IEEE Press, Athens, Greece. [PDF].

Didi, S., and Nitschke, G. (2016). Hybridizing Novelty Search for Transfer Learning. In Proceedings of the IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2016), pages 2620-2628, IEEE Press, Athens, Greece. [PDF].

Shorten, D., and Nitschke, G. (2016). The Relationship Between Evolvability and Robustness in the Evolution of Boolean Networks. In Proceedings of the 15th International Conference on the Synthesis and Simulation of Living Systems (ALIFE VX), pages 276-283, MIT Press, Cancun, Mexico. [PDF].

Shorten, D., and Nitschke, G. (2016). The Evolution of Evolvability in Evolutionary Robotics. In Proceedings of the 15th International Conference on the Synthesis and Simulation of Living Systems (ALIFE VX), pages 260-267, MIT Press, Cancun, Mexico. [PDF].

Didi, S., and Nitschke, G. (2016). Neuro-Evolution for Multi-Agent Policy Transfer in RoboCup Keep-Away. In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2016), pages 1281-1282, ACM, Singapore. [PDF].

Didi, S., and Nitschke, G. (2016). Multi-Agent Behavior-Based Policy Transfer. In Proceedings of the European Conference on the Applications of Evolutionary Computation (Evostar 2016), pages 181-197, Springer, Porto, Portugal. [PDF].

Hewland, J., and Nitschke, G. (2015). The Benefits of Adaptive Behavior and Morphology for Cooperation in Robot Teams. In Proceedings of the IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2015), pages 1047-1054, IEEE Press, Cape Town, South Africa. [PDF].

Watson, J., and Nitschke, G. (2015). Evolving Robust Robot Team Morphologies for Collective Construction. In Proceedings of the IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2015), pages 1039-1046, IEEE Press, Cape Town, South Africa. [PDF].

Wang, S., Gain, J., and Nitschke, G. (2015). Controlling Crowd Simulations using Neuro-Evolution. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2015), pages 353-360, ACM Press, Madrid, Spain. [PDF].

Huang, A., Nitschke, G., and Shorten, D. (2015). Searching for Novelty in Pole Balancing. In Proceedings of the IEEE Congress on Evolutionary Computation (IEEE CEC 2015), pages 1792-1798, IEEE Press, Sendai, Japan. [PDF].

Watson, J., and Nitschke, G. (2015). Deriving Minimal Sensory Configurations for Evolved Cooperative Robot Teams. In Proceedings of the IEEE Congress on Evolutionary Computation (IEEE CEC 2015), pages 3065-3071, IEEE Press, Sendai, Japan. [PDF].

Shorten, D., and Nitschke, G. (2015). Evolving Generalised Maze Solvers. In Proceedings of the 18th European Conference on the Applications of Evolutionary Computation (Evostar 2015), pages 783-794, Springer, Copenhagen, Denmark. [PDF].

Shorten, D., and Nitschke, G. (2014). How evolvable is novelty search?. In Proceedings of the IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2014), pages 125-132, IEEE Press, Orlando, USA. [PDF].

Wang, S., Gain, J., and Nitschke, G. (2014). Comparing Crossover Operators in Neuro-Evolution with Crowd Simulations. In Proceedings of the IEEE Congress on Evolutionary Computation (IEEE CEC 2014), pages 298 - 2305, IEEE Press, Beijing, China. [PDF].

Shorten, D., and Nitschke, G. (2014). Generational Neuro-Evolution: Restart and Retry for Improvement. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2014), pages 225 - 232, ACM Press, Vancouver, Canada. [PDF].

Nitschke, G., van Heerden, W., and Agwang, F. (2014). Lifetimes of Migration Behavior. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2014). pages 25 - 26, ACM Press, Vancouver, Canada. [PDF].

Nitschke, G., and Witkowski, O. (2013). The Transmission of Migratory Behaviors. In Proceedings of the twelfth European Conference on the Synthesis and Simulation of Living Systems: Advances in Artificial Life (ECAL 2013), pages 1218 - 1220. MIT Press, Taormina, Italy. [PDF].

Goss, R., and Nitschke, G. (2013). Network Protocol Identification Ensemble with EA Optimization. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2013), pages 1735 - 1736, ACM Press, Amsterdam, the Netherlands. [PDF].

Nitschke, G., and Tolkamp, M. (2013). Approaches to Dynamic Team Sizes. In Proceedings of the IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2013), pages 66 - 73. IEEE Press, Singapore. [PDF].

Goss, R., and Nitschke, G. (2013). Automated Network Application Classification: A Competitive Learning Approach. In Proceedings of the IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2013), pages 45 - 52, IEEE Press, Singapore. [PDF].

Ikegami, T., Nitschke, G., and Witkowski, O. (2012). When is Happy Hour: An Agent’s Concept of Time. In Proceedings of Artificial Life XIII: The Thirteenth International Conference on the Synthesis and Simulation of Living Systems, pages 544 - 546. MIT Press, East Lansing, USA. [PDF].

Nitschke, G. (2012). Behavioral Heterogeneity and Collective Construction. In Proceedings of the IEEE Congress on Evolutionary Computation (IEEE CEC 2012). pages 387-394, IEEE Press, Brisbane, Australia. [PDF].

De Bruyn, C., Nitschke, G., and van Heerden, W. (2011). Evolutionary Algorithms and Particle Swarm Optimization for Artificial Language Evolution. In Proceedings of the IEEE Congress on Evolutionary Computation (IEEE CEC 2011), pages 1110-1108, IEEE Press, New Orleans, USA. [PDF].

Viljoen, C., Nitschke, G., and van Heerden, W. (2011). Evolution of a Fictional Dialogue. In Proceedings of the IEEE Congress on Evolutionary Computation (IEEE CEC 2011), pages 1108-1116, IEEE Press, New Orleans, USA. [PDF].

Langenhoven, L., and Nitschke, G. (2010). Neuro-Evolution for Competitive Co-evolution of Biologically Canonical Predator and Prey Behaviors. In Proceedings of the Second World Congress on Nature and Biologically Inspired Computing, pages 553-560, IEEE Press, Kitakyushu, Japan. [PDF].

Langenhoven, L., and Nitschke, G. (2010). Neuro-evolution versus particle swarm optimization for competitive co-evolution of pursuit-evasion behaviors. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2010), pages 3452-3459, IEEE Press, Barcelona, Spain. [PDF].

Castillo, C., Engelbrecht, A., and Nitschke, G. (2009). Niche Particle Swarm Opitmization for Neural Network Ensembles. In Proceedings of the 10th European Conference on Artificial Life (ECAL 2009), pages 889-907, Springer, Budapest, Hungary. [PDF].

Nitschke, G. (2009). Neuro-Evolution Methods for Gathering and Collective Construction. In Proceedings of the 10th European Conference on Artificial Life (ECAL 2009), pages 111-119, Springer, Budapest, Hungary. [PDF].

Nitschke, G. (2009). Neuro-Evolution Approaches to Collective Behavior. In Proceedings of the IEEE Congress on Evolutionary Computation (IEEE CEC 2009), pages 249-257, IEEE Press, Trondheim, Norway. [PDF].

van Krevelen, D., and Nitschke, G. (2008). Neuro-Evolution for a Gathering and Collective Construction Task. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2008), pages 225-232, ACM Press, Atlanta, USA. [PDF].

Nitschke, G., and Schut, M. (2008). Designing Multi-Rover Emergent Specialization. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2008), pages 233-240, ACM Press, Atlanta, USA. [PDF].

Nitschke, G., Schut, M., and Eiben, A. (2007). Emergent specialization in the extended multi-rover problem. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2007), pages 189-195, IEEE Press, Singapore. [PDF].

Nitschke, G. (2007). Neuro-evolution Methods for Designing Emergent Specialization. In Proceedings of the Ninth European Conference on Artificial Life (ECAL 2007), pages 1120-1130, Springer, Lisbon, Portugal.

Eiben, A., Nitschke, G., and Schut, M. (2007). Evolutionary Design of Specialization. In Proceedings of the First IEEE Symposium on Artificial Life (ALIFE'07), pages: 417-424. IEEE Press, Hawaii, USA. [PDF].

Buresch, T., Eiben, A., Nitschke, G., and Schut, M. (2005). Effects of evolutionary and lifetime learning on minds and bodies in an artifical society. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2005), pages: 1448-1454. IEEE Press, Edinburgh, United Kingdom. [PDF].

Eiben, A., Nitschke, G., and Schut, M. (2005). Evolving an agent collective for cooperative mine sweeping. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2005), pages: 831-836. IEEE Press, Edinburgh, United Kingdom. [PDF].

Eiben, A., Nitschke, G., and Schut, M. (2005). Comparative Reproduction Schemes for Evolving Gathering Collectives. In Proceedings of the Eighth European Conference on Artificial Life (ECAL 2005), pages: 795-804. Springer, Canterbury, United Kingdom. [PDF].

Nitschke, G. (2003). Emergence of Cooperation in a Pursuit-Evasion Game. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI 2003), pages 639-646, AAAI Press, Acapulco, Mexico. [PDF].


Workshop Proceedings

Eiben, A., Nitschke, G., and Schut, M. (2006). Collective specialization for evolutionary design of a multi-robot system. In Proceedings of the Second International Workshop on Swarm Robotics, pages 189-206, Springer, Rome, Italy. [PDF].

Nitschke, G. (2004). Emergence of Cooperation in Swarm Systems. In Proceedings of the Fourth International Workshop on Swarm Intelligence and Patterns, pages: 4-10. IEEE Press, Budapest, Hungary. [PDF].



Thesis

Nitschke, G. (2009). Neuro-Evolution for Emergent Specialization in Collective Behavior Systems. PhD Thesis. Vrije Universiteit Amsterdam. Amsterdam, The Netherlands. [PDF].