Emojinating: Evolving Emoji Blends

Graphic designers visually represent concepts in several of their daily tasks, such as in icon design. Computational systems can be of help in such tasks by stimulating creativity. However, current computational approaches to concept visual representation lack in effectiveness in promoting the exploration of the space of possible solutions. In this paper, we present an evolutionary approach that combines a standard Evolutionary Algorithm with a method inspired by Estimation of Distribution Algorithms to evolve emoji blends to represent user-introduced concepts. The quality of the developed approach is assessed using two separate user-studies. In comparison to previous approaches, our evolutionary system is able to better explore the search space, obtaining solutions of higher quality in terms of concept representativeness.

[1]  Sérgio M. Rebelo,et al.  Evolutionary Experiments in the Development of Typographical Posters , 2018 .

[2]  Gerry V. Dozier,et al.  An interactive distributed evolutionary algorithm (IDEA) for design , 2005, 2005 IEEE International Conference on Systems, Man and Cybernetics.

[3]  Penousal Machado,et al.  Using Image Schemas in the Visual Representation of Concepts , 2018, TriCoLore.

[4]  Ping Xiao,et al.  Vismantic: Meaning-making with Images , 2015, ICCC.

[5]  Adam Kelly Piper Participatory design of warning symbols using distributed interactive evolutionary computation , 2009 .

[6]  Julian Togelius,et al.  Sentient Sketchbook: Computer-aided game level authoring , 2013, FDG.

[7]  Penousal Machado,et al.  Emojinating : Representing Concepts Using Emoji , 2018 .

[8]  Charles Browne A New General Service List: The Better Mousetrap We've Been Looking for? , 2014 .

[9]  Brian Magerko,et al.  Co-Creative Drawing Agent with Object Recognition , 2016, AIIDE.

[10]  Jie Yan,et al.  A Review of Gait Optimization Based on Evolutionary Computation , 2010, Appl. Comput. Intell. Soft Comput..

[11]  Amílcar Cardoso,et al.  The Boat-House Visual Blending Experience , 2002 .

[12]  Douglas Eck,et al.  A Neural Representation of Sketch Drawings , 2017, ICLR.

[13]  Amy Beth Warriner,et al.  Concreteness ratings for 40 thousand generally known English word lemmas , 2014, Behavior research methods.

[14]  David E. Goldberg,et al.  A Survey of Optimization by Building and Using Probabilistic Models , 2002, Comput. Optim. Appl..

[15]  Nuno Lourenço,et al.  EvoFashion: Customising Fashion Through Evolution , 2017, EvoMUSART.

[16]  Nuno Lourenço,et al.  Interactive Evolution of Swarms for the Visualisation of Consumptions , 2018, ArtsIT/DLI.

[17]  R. Malina Aaron’s Code: Meta-Art, Artificial Intelligence and the Work of Harold Cohen by Pamela McCorduck (review) , 2017 .

[18]  Penousal Machado,et al.  How Shell and Horn make a Unicorn: Experimenting with Visual Blending in Emoji , 2018, ICCC.

[19]  I. C. Parmee,et al.  User-Centric Evolutionary Computing: Melding Human and Machine Capability to Satisfy Multiple Criteria , 2008, Multiobjective Problem Solving from Nature.

[20]  Yong Jae Lee,et al.  ShadowDraw: real-time user guidance for freehand drawing , 2011, ACM Trans. Graph..

[21]  Tiago Martins,et al.  X-Faces: The eXploit Is Out There , 2016, ICCC.

[22]  Penousal Machado,et al.  Fitness and Novelty in Evolutionary Art , 2016, EvoMUSART.

[23]  Penousal Machado,et al.  A Pig, an Angel and a Cactus Walk Into a Blender: A Descriptive Approach to Visual Blending , 2017, ICCC.

[24]  Amit P. Sheth,et al.  EmojiNet: An Open Service and API for Emoji Sense Discovery , 2017, ICWSM.

[25]  Pegah Karimi,et al.  A computational model for visual conceptual blends , 2019, IBM J. Res. Dev..

[26]  Tomoyuki Hiroyasu,et al.  Discussion of a Crossover Method using a Probabilistic Model for interactive Genetic Algorithm , 2008 .

[27]  Brian Carnahan,et al.  Interactive evolutionary design of anthropomorphic symbols , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[28]  Catherine Havasi,et al.  Representing General Relational Knowledge in ConceptNet 5 , 2012, LREC.