The Role of Emotion and Communication in Cooperative Behavior
Active from 2013 - 2016
The main hypothesis is that complex cooperative behavior arises through a principled interaction between emotion and communication. A primary emotion such as fearfulness results in avoiding the risky actions necessary for the task. This emotion is overcome through a second emotion, affiliation to the team. This emotion also enhances communication, which would otherwise be obscured by fear, so that the actions can be effectively coordinated. To evaluate the hypothesis, a computer scientist will join forces with a behavioral biologist in the proposed project. The approach is based on the principle that, to understand such behavior, it is useful to understand its evolutionary origins. This perspective leads to a unique methodology: using computational evolution to analyze and draw conclusions from an animal model. Specifically, the project focuses on the complex cooperation that emerges in spotted hyenas of Eastern Africa (Crocuta crocuta) when they compete for food resources with larger and more powerful animals, i.e. lions. The specific aims are to: (1) Characterize the target behavior and its endocrine correlates in detail in the animal model; (2) build a computational model that replicates the behavior; (3) determine how the behavior is produced in the model; (4) understand the evolutionary origins of the behavior; and (5) determine how problems with the behavior can be ameliorated. The end result will be a computationally verified theory of how emotions and communication mediate sophisticated cooperative behavior in mammals, and why it occurs this way. This research is supported by NIH under grant 5R01GM105042-02.
Joel Lehman Postdoctoral Fellow joel [at] cs utexas edu
Dan Lessin Ph.D. Student dlessin [at] cs utexas edu
Xun Li Ph.D. Student xun bhsfer [at] cs utexas edu
Padmini Rajagopalan Ph.D. Student padmini [at] cs utexas edu
Aditya Rawal Ph.D. Student aditya [at] cs utexas edu
Jacob Schrum Ph.D. Alumni schrum2 [at] southwestern edu
Risto Miikkulainen Faculty risto [at] cs utexas edu
Adapting Morphology to Multiple Tasks in Evolved Virtual Creatures 2014
Dan Lessin, Don Fussell, Risto Miikkulainen, To Appear In Proceedings of The Fourteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE 14) 2014 2014.
Evolution of Communication in Mate Selection 2014
Aditya Rawal, Janette Boughman and Risto Miikkulainen, To Appear In Proceedings of The Fourteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE 14) , New York, USA, July, 2014 2014.
Evolving Multimodal Behavior Through Modular Multiobjective Neuroevolution 2014
Jacob Schrum, PhD Thesis, The University of Texas at Austin. Tech Report TR-14-07.
Evolving Multimodal Behavior Through Subtask and Switch Neural Networks 2014
Xun Li, Risto Miikkulainen, Proceedings of The Fourteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE 14) (2014).
Evolving Multimodal Behavior With Modular Neural Networks in Ms. Pac-Man 2014
Jacob Schrum and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2014), pp. 325--332, Vancouver, BC, Canada, July 2014. Best Paper: Digital Entertainment and Arts.
General Intelligence through Prolonged Evolution of Densely Connected Neural Networks 2014
Padmini Rajagopalan, Aditya Rawal, Kay E. Holekamp and Risto Miikkulainen, To Appear In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2014), Vancouver, BC, Canada, July 2014.
Overcoming Deception in Evolution of Cognitive Behaviors 2014
Joel Lehman and Risto Miikkulainen, To Appear In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2014), Vancouver, BC, Canada, July 2014.
The Evolution of General Intelligence 2014
Padmini Rajagopalan, Kay E. Holekamp and Risto Miikkulainen, To Appear In Proceedings of The Fourteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE 14), New York, NY 2014.
Trading Control Intelligence for Physical Intelligence: Muscle Drives in Evolved Virtual Creatures 2014
Dan Lessin, Don Fussell, Risto Miikkulainen, To Appear In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) 2014 2014.
MM-NEAT Modular Multiobjective NEAT is a software framework in Java that builds on the basic principles of 2014

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