When rats rescue robots

Quinn, Laleh K.; Schuster, Luisa P.; Aguilar‐Rivera, Marcelo; Arnold, Josh; Ball, David; Gygi, Emmanuel; Holt, Jesse R.; Lee, Daeun J.; Taufatofua, Jonathon; Wiles, Janet; Chiba, Andrea A.

doi:10.26451/abc.05.04.04.2018

Cited by 23 publications

(22 citation statements)

References 13 publications

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“…In a robotic variation of the empathy experiment, a rat was trapped in a cage interacted with two different robots, one of which was helpful and opened the cage and the other of which was uncooperative and ignored the trapped rat (Quinn et al, 2018 ). Interestingly, the rat remembered who its robot friends were.…”

Section: Behavioral Trade-offs - Contextual Decision-makingmentioning

confidence: 99%

Design Principles for Neurorobotics

Krichmar

Hwu²

2022

Front. Neurorobot.

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In their book “How the Body Shapes the Way We Think: A New View of Intelligence,” Pfeifer and Bongard put forth an embodied approach to cognition. Because of this position, many of their robot examples demonstrated “intelligent” behavior despite limited neural processing. It is our belief that neurorobots should attempt to follow many of these principles. In this article, we discuss a number of principles to consider when designing neurorobots and experiments using robots to test brain theories. These principles are strongly inspired by Pfeifer and Bongard, but build on their design principles by grounding them in neuroscience and by adding principles based on neuroscience research. Our design principles fall into three categories. First, organisms must react quickly and appropriately to events. Second, organisms must have the ability to learn and remember over their lifetimes. Third, organisms must weigh options that are crucial for survival. We believe that by following these design principles a robot's behavior will be more naturalistic and more successful.

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Section: Behavioral Trade-offs - Contextual Decision-makingmentioning

confidence: 99%

Design Principles for Neurorobotics

Krichmar

Hwu²

2022

Front. Neurorobot.

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“…The iRAT (Wiles, Heath, Ball, Quinn, & Chiba, 2012), the PoulBot (Gribovskiy, Halloy, Deneubourg, Bleuler, & Mondada, 2010) and the robotic cockroach (Halloy et al, 2007) had the same size as an adult rat (Rattus norvegicus), chicken (Gallus gallus domesticus) or cockroaches (respectively), but, even for an untrained human eye, they looked rather different from the conspecific animal partner. In these cases, the rather limited resemblance was partly due to constraints of the technology, and investigators aimed to balance this by adding smells in the case of the iRAT (Quinn et al, 2018) and the robotic cockroach in order to increase the chance of interaction.…”

Section: Embodimentmentioning

confidence: 99%

Methodological challenges of the use of robots in ethological research

Abdai¹,

Korcsok²,

Köröndi³

et al. 2018

AB&C

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Artificial models have been used as interactive partners for decades to study the social behavior of animals. Recent technological developments have opened up novel possibilities by allowing researchers to use remote controlled and autonomous objects in these studies, and Animal-Robot Interaction has become an emerging field of behavior science. However, there are theoretical, methodological and practical issues in ethological research using robotic agents. Here we aimed to provide an overview on robots by classifying them along different aspects to facilitate future research, and to present some novel approaches that could be considered as a guide for researchers who are new to the fields of animal-robot interactions (ARI) and human-robot interactions (HRI). The present review may facilitate future collaboration between biologists/psychologists, robot developers, engineers and programmers that further contributes to the development of novel research methods and procedures.

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“…This brought about the question of whether iRat could be driven to behave in a socially interactive manner that would result in rats engaging in prosocial behavior with the iRat as they do with conspecifics (Rutte & Taborsky, 2008;Bartal et al, 2011). Quinn et al (2018) used the iRat to interact with rats for the purpose of eliciting social responses and examining prosocial behavior towards robots (For Artists Depiction and Picture of Live Interaction See Figure 1). Rats will not only engage in prosocial behaviors with each other, such as freeing other rats from an enclosed restrainer, but have also been shown to reciprocate with robots (Quinn, et al 2018, Wiles et al, 2012.…”

Section: Introductionmentioning

confidence: 99%

“…Quinn et al (2018) used the iRat to interact with rats for the purpose of eliciting social responses and examining prosocial behavior towards robots (For Artists Depiction and Picture of Live Interaction See Figure 1). Rats will not only engage in prosocial behaviors with each other, such as freeing other rats from an enclosed restrainer, but have also been shown to reciprocate with robots (Quinn, et al 2018, Wiles et al, 2012.…”

Section: Introductionmentioning

confidence: 99%

“…The target of the explanation is the behavior of the living system in response to the robotic agent. A key aspect of interactive biorobotics is the integration and habituation of living systems to interactive robot counterparts (Quinn et al 2018, Datteri, 2020). A popular example of an interactive biorobotics paradigm with animals was the Waseda Rat, a rat-like robot that continuously chases a living rat to induce anxiety-like behavior (Ishii et al, 2006; Shi et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

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Interactive Neurorobotics: Behavioral and Neural Dynamics of Agent Interactions

Leonardis

Breston

Lucero-Moore

et al. 2022

Preprint

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Interactive neurorobotics is a subfield which characterizes brain responses evoked during interaction with a robot, and their relationship with the behavioral responses. Gathering rich neural and behavioral data from humans or animals responding to agents can act as a scaffold for the design process of future social robots. The goals of this research can be broadly broken down into two categories. The first, seeks to directly study how organisms respond to artificial agents in contrast to biological or inanimate ones. The second, uses the novel affordances of the robotic platforms to investigate complex phenomena, such as responses to multisensory stimuli during minimally structured interactions, that would be difficult to capture with classical experimental setups. Here we argue that to realize the full potential of the approach, both goals must be integrated through methodological design that is informed by a deep understanding of the model system, as well as engineering and analytical considerations. We then propose a general framework for such experiments that emphasizes naturalistic interactions combined with multimodal observations and complementary analysis pipelines that are necessary to render a holistic picture of the data for the purpose of informing robotic design principles. Finally, we demonstrate this approach with an exemplar rat-robot social interaction task which included simultaneous multi-agent tracking and neural recordings.

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When rats rescue robots

Cited by 23 publications

References 13 publications

Design Principles for Neurorobotics

Design Principles for Neurorobotics

Methodological challenges of the use of robots in ethological research

Interactive Neurorobotics: Behavioral and Neural Dynamics of Agent Interactions

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