Robots with Internal Models: A Route to Self-Aware and Hence Safer Robots

Winfield, Alan F. T.

doi:10.1142/9781783264186_0016

Cited by 23 publications

(20 citation statements)

References 17 publications

(15 reference statements)

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“…Other work focuses on the importance of providing robots with internal models to make them self-aware which will lead to enhanced safety and potentially also ethical behavior in Winfield (2014). It could also be advantageous for multiple robots to share parts of their internally modeled behavior with each other (Winfield, 2017).…”

Section: Programs Undertaking Ethical Decision-makingmentioning

confidence: 99%

A Review of Future and Ethical Perspectives of Robotics and AI

Tørresen

2018

Front. Robot. AI

128

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In recent years, there has been increased attention on the possible impact of future robotics and AI systems. Prominent thinkers have publicly warned about the risk of a dystopian future when the complexity of these systems progresses further. These warnings stand in contrast to the current state-of-the-art of the robotics and AI technology. This article reviews work considering both the future potential of robotics and AI systems, and ethical considerations that need to be taken in order to avoid a dystopian future. References to recent initiatives to outline ethical guidelines for both the design of systems and how they should operate are included.

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Section: Programs Undertaking Ethical Decision-makingmentioning

confidence: 99%

A Review of Future and Ethical Perspectives of Robotics and AI

Tørresen

2018

Front. Robot. AI

128

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“…and, ... 2. of several possible next actions x i , which should I choose?" (Winfield, 2014) Holland writes: an Internal Model allows a system to look ahead to the future consequences of current actions, without actually committing itself to those actions (Holland, 1992, p. 25). This leads to the idea of "an internal model as a consequence engine-a mechanism for predicting and hence anticipating the consequences of actions" .…”

Section: Simulation-based Internal Modelingmentioning

confidence: 99%

Experiments in Artificial Theory of Mind: From Safety to Story-Telling

Winfield

2018

Front. Robot. AI

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Theory of mind is the term given by philosophers and psychologists for the ability to form a predictive model of self and others. In this paper we focus on synthetic models of theory of mind. We contend firstly that such models-especially when tested experimentally-can provide useful insights into cognition, and secondly that artificial theory of mind can provide intelligent robots with powerful new capabilities, in particular social intelligence for human-robot interaction. This paper advances the hypothesis that simulation-based internal models offer a powerful and realisable, theory-driven basis for artificial theory of mind. Proposed as a computational model of the simulation theory of mind, our simulation-based internal model equips a robot with an internal model of itself and its environment, including other dynamic actors, which can test (i.e., simulate) the robot's next possible actions and hence anticipate the likely consequences of those actions both for itself and others. Although it falls far short of a full artificial theory of mind, our model does allow us to test several interesting scenarios: in some of these a robot equipped with the internal model interacts with other robots without an internal model, but acting as proxy humans; in others two robots each with a simulation-based internal model interact with each other. We outline a series of experiments which each demonstrate some aspect of artificial theory of mind.

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“…The architecture discussed here is based upon the Consequence Engine (CE) (Winfield, 2014;Winfield et al, 2014;Vanderelst and Winfield, 2017). A schematic view of this architecture is shown in The CE allows the robot to evaluate the consequences of each of its next possible actions, which are executed inside the simulator contained in the CE using an internal model, after which the consequences of every action are evaluated in turn.…”

Section: Architecturementioning

confidence: 99%

“…In previous work, we proposed a simulation-based internal model architecture (Winfield, 2014) centered upon what we call a Consequence Engine (CE). To demonstrate the effectiveness of the CE approach for safety, we have undertaken a series of experiments involving one smart (as in using a CE) robot and several other (i.e., Braitenberg style) robots acting as proxy-humans in our scenario.…”

Section: Introductionmentioning

confidence: 99%

Simulation-Based Internal Models for Safer Robots

2018

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In this paper, we explore the potential of mobile robots with simulation-based internal models for safety in highly dynamic environments. We propose a robot with a simulation of itself, other dynamic actors and its environment, inside itself. Operating in real time, this simulation-based internal model is able to look ahead and predict the consequences of both the robot's own actions and those of the other dynamic actors in its vicinity. Hence, the robot continuously modifies its own actions in order to actively maintain its own safety while also achieving its goal. Inspired by the problem of how mobile robots could move quickly and safely through crowds of moving humans, we present experimental results which compare the performance of our internal simulation-based controller with a purely reactive approach as a proof-of-concept study for the practical use of simulation-based internal models.

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Robots with Internal Models: A Route to Self-Aware and Hence Safer Robots

Cited by 23 publications

References 17 publications

A Review of Future and Ethical Perspectives of Robotics and AI

A Review of Future and Ethical Perspectives of Robotics and AI

Experiments in Artificial Theory of Mind: From Safety to Story-Telling

Simulation-Based Internal Models for Safer Robots

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