Identifying Necessary Conditions for Open-Ended Evolution through the Artificial Life World of Chromaria

Soros, L. B.; Stanley, Kenneth O.

doi:10.7551/978-0-262-32621-6-ch128

Cited by 57 publications

(57 citation statements)

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“…Defining a more general measure, applicable to OEE, appears to be a major research challenge, but potentially a rewarding one. Further work is required to understand the similarities and differences between novelty search and OEE; one line of research along these lines has recently been initiated by Soros and Stanley [44].…”

Section: Themes From the Open Discussionmentioning

confidence: 99%

Open-Ended Evolution: Perspectives from the OEE Workshop in York

Taylor¹,

Bedau²,

Channon³

et al. 2016

Artificial Life

104

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We describe the content and outcomes of the First Workshop on Open-Ended Evolution: Recent Progress and Future Milestones (OEE1), held during the ECAL 2015 conference at the University of York, UK, in July 2015. We briefly summarize the content of the workshopʼs talks, and identify the main themes that emerged from the open discussions. Two important conclusions from the discussions are: (1) the idea of pluralism about OEE-it seems clear that there is more than one interesting and important kind of OEE; and (2) the importance of distinguishing observable behavioral hallmarks of systems undergoing OEE from hypothesized underlying mechanisms that explain why a system exhibits those hallmarks. We summarize the different hallmarks and mechanisms discussed during the workshop, and list the specific systems that were highlighted with respect to particular hallmarks and mechanisms. We conclude by identifying some of the most important open research questions about OEE that are apparent in light of the discussions. The York workshop provides a foundation for a follow-up OEE2 workshop taking place at the ALIFE XV conference in Cancún, Mexico, in July 2016. Additional materials from the York workshop, including talk abstracts, presentation slides, and videos of each talk, are available at http://alife.org/ws/oee1.

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Section: Themes From the Open Discussionmentioning

confidence: 99%

Open-Ended Evolution: Perspectives from the OEE Workshop in York

Taylor¹,

Bedau²,

Channon³

et al. 2016

Artificial Life

104

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“…Bedau et al (2000), Soros and Stanley (2014), and Taylor et al (2016) and others identified open-ended adaptation in artificial evolutionary systems as one of the big questions of artificial life. Open-ended adaptation in artificial systems, in particular in combination with learning relevant task behavior, has proved to be an elusive ambition.…”

Section: Benchmarksmentioning

confidence: 99%

Embodied Evolution in Collective Robotics: A Review

2018

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This article provides an overview of evolutionary robotics techniques applied to online distributed evolution for robot collectives, namely, embodied evolution. It provides a definition of embodied evolution as well as a thorough description of the underlying concepts and mechanisms. This article also presents a comprehensive summary of research published in the field since its inception around the year 2000, providing various perspectives to identify the major trends. In particular, we identify a shift from considering embodied evolution as a parallel search method within small robot collectives (fewer than 10 robots) to embodied evolution as an online distributed learning method for designing collective behaviors in swarm-like collectives. This article concludes with a discussion of applications and open questions, providing a milestone for past and an inspiration for future research.

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“…In the larger field of Artificial Life (ALife) there has been a move toward characterizing the conditions under which open-ended evolution [12] can occur [6,13,14]. This in turn has added steam to a growing realization that the fitness or objective functions used to drive the artificial evolution of agents (robots in the case of ER) may be incompatible with open-ended evolution [8,15,16].…”

Section: Introductionmentioning

confidence: 99%

“…There is now, and has been for the last decade, considerable pressure in the ER community to generate controllers capable of demonstrably complex behaviors. Within this context, and considering that benchmark ER tasks have in most cases been studied and reproduced many times, researchers and theorists have begun to ask why it is the case that ER methods have not produced complex situated agents [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Embodied artificial life at an impasse can evolutionary robotics methods be scaled?

Nelson¹

2014

2014 IEEE Symposium on Evolving and Autonomous Learning Systems (EALS)

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Abstract-Evolutionary robotics (ER) investigates the application of artificial evolution toward the synthesis of robots capable of performing autonomous behaviors. Over the last 25 years, researchers have reported increasingly complex evolved behaviors, and have compiled a de facto set of benchmark tasks. Perhaps the best known of these is the obstacle avoidance and target homing task performed by differential drive robots. More complex tasks studied in recent ER work include augmented variants of the rodent T-maze and complex foraging tasks. But can proof-of-concept results such as these be extended to evolve complex autonomous behaviors in a general sense? In this topical analysis paper we survey relevant research and make the case that common tasks used to demonstrate the effectiveness of evolutionary robotics are not characteristic of more general cases and in fact do not fully prove the concept that artificial evolution can be used to evolve sophisticated autonomous agent behaviors. Robots capable of performing many of the tasks studied in ER have now been evolved using nearly aggregate binary success/fail fitness functions. However, arguments used to support the necessity of incremental methods for complex tasks are essentially sound. This raises the possibility that the tasks themselves allow for relatively simple solutions, or span a relatively small candidate solution set. This paper presents these arguments in detail and concludes with a discussion of current ER research.

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Identifying Necessary Conditions for Open-Ended Evolution through the Artificial Life World of Chromaria

Cited by 57 publications

References 0 publications

Open-Ended Evolution: Perspectives from the OEE Workshop in York

Open-Ended Evolution: Perspectives from the OEE Workshop in York

Embodied Evolution in Collective Robotics: A Review

Embodied artificial life at an impasse can evolutionary robotics methods be scaled?

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