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Proceedings Papers
. isal2024, ALIFE 2024: Proceedings of the 2024 Artificial Life Conference60, (July 22–26, 2024) 10.1162/isal_a_00789
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Artificial Life (ALife) as an interdisciplinary field draws inspiration and influence from a variety of perspectives. Scientific progress crucially depends, then, on concerted efforts to invite cross-disciplinary dialogue. The goal of this paper is to revitalize discussions of potential connections between the fields of Computational Creativity (CC) and ALife, focusing specifically on the concept of Open-Endedness (OE); the primary goal of CC is to endow artificial systems with creativity, and ALife has dedicated much research effort into studying and synthesizing OE and artificial innovation. However, despite the close proximity of these concepts, their use so far remains confined to their respective communities, and their relationship is largely unclear. We provide historical context for research in both domains, and review the limited work connecting research on creativity and OE explicitly. We then highlight specific questions to be investigated in future work, with the eventual goals of (i) decreasing conceptual ambiguity by highlighting similarities and differences between the concepts of OE and creativity, (ii) identifying synergy effects of a research agenda that encompasses both concepts, and (iii) establishing a dialogue between ALife and CC research.
Proceedings Papers
. isal2023, ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference129, (July 24–28, 2023) 10.1162/isal_a_00580
Proceedings Papers
. isal2022, ALIFE 2022: The 2022 Conference on Artificial Life15, (July 18–22, 2022) 10.1162/isal_a_00493
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The concept of evolvability, that is the capacity to produce heritable and adaptive phenotypic variation, is crucial in the current understanding of evolution. However, while its meaning is intuitive, there is no consensus on how to quantitatively measure it. As a consequence, in evolutionary robotics, it is hard to evaluate the interplay between evolvability and fitness and its dependency on key factors like the evolutionary algorithm (EA) or the representation of the individuals. Here, we propose to use MAP-Elites, a well-established Quality Diversity EA, as a support structure for measuring evolvability and for highlighting its interplay with fitness. We map the solutions generated during the evolutionary process to a MAP-Elites-like grid and then visualize their fitness and evolvability as maps. This procedures does not affect the EA execution and can hence be applied to any EA: it only requires to have two descriptors for the solutions that can be used to meaningfully characterize them. We apply this general methodology to the case of Voxel-based Soft Robots (VSR), a kind of modular robots with a body composed of uniform elements whose volume is individually varied by the robot brain. Namely, we optimize the robots for the task of locomotion using evolutionary computation. We consider four representations, i.e., ways of transforming a genotype into a robot, two for the brain only and two for both body and brain of the VSR, and two EAs (MAP-Elites and a simple evolutionary strategy) and examine the evolvability and fitness maps. The experiments suggest that our methodology permits us to discover interesting patterns in the maps: fitness maps appear to depend more on the representation of the solution, whereas evolvability maps appear to depend more on the EA. As an aside, we find that MAP-Elites is particularly effective in the simultaneous evolution of the body and the brain of Voxel-based Soft Robots.
Proceedings Papers
. ecal2017, ECAL 2017, the Fourteenth European Conference on Artificial Life553-560, (September 4–8, 2017) 10.1162/isal_a_088
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Developing a comprehensive theory of open-ended evolution (OEE) depends critically on understanding the mechanisms underlying the major evolutionary transitions; such periods of rapid innovation, such as the Cambrian explosion, have resulted in exactly the kind of diversity and complexity deemed the hallmarks of strong OEE. This paper introduces a new domain for studying major transitions in an evolutionary robotics context. Inspired by the popular Minecraft video game, the new Voxelbuild domain centers on agents that evolve the capacity to build arbitrarily complex block structures with minimal objectives. Initial experiments demonstrate both the rich expressive potential of the new domain and, intriguingly, the occurrence of major evolutionary transitions in at least some runs, thereby providing a unique opportunity to probe how and why such transitions occur or fail to occur in different runs of the same system.
Proceedings Papers
. alif2016, ALIFE 2016, the Fifteenth International Conference on the Synthesis and Simulation of Living Systems208-215, (July 4–6, 2016) 10.1162/978-0-262-33936-0-ch040
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Because the kind of open-ended complexity explosion seen on Earth remains beyond the observed dynamics of current artificial life worlds, it has become critical to isolate and investigate specific factors that may contribute to open-endedness. This paper focuses on one such factor that has previously received little attention in research on open-endedness: the minimal criterion (MC) for reproduction. Originally proposed as an enhancement to novelty search, the MC is in effect a different abstraction of evolution than the more conventional competition-focused fitness-based paradigm, instead focusing on the minimal task that must be completed for an organism to be allowed to produce offspring. The MC is interesting for studying open-endedness because in principle its strictness (i.e. how hard it is to satisfy) can be varied on a continuum to observe its effects. While in many artificial life worlds the MC strictness is implicit and therefore difficult to vary systematically, in the previously-introduced Chromaria world, the MC is designed to be set explicitly by the experimenter, making possible the systematic study of different levels of MC strictness in this paper. The main result, supported by visual, quantitative, and qualitative observations, is that the strictness of the MC can profoundly affect open- ended dynamics, ultimately deciding between complete stagnation (both with extreme strictness or complete relaxation) and orderly divergence. This result offers a lesson of particular importance to worlds whose MCs are not explicit by exposing an area of sensitivity within open-ended systems that is easy to overlook because of its implicit nature.