Memory and mental time travel in humans and social robots

Abstract

From neuroscience, brain imaging and the psychology of memory, we are beginning to assemble an integrated theory of the brain subsystems and pathways that allow the compression, storage and reconstruction of memories for past events and their use in contextualizing the present and reasoning about the future—mental time travel (MTT). Using computational models, embedded in humanoid robots, we are seeking to test the sufficiency of this theoretical account and to evaluate the usefulness of brain-inspired memory systems for social robots. In this contribution, we describe the use of machine learning techniques—Gaussian process latent variable models—to build a multimodal memory system for the iCub humanoid robot and summarize results of the deployment of this system for human–robot interaction. We also outline the further steps required to create a more complete robotic implementation of human-like autobiographical memory and MTT. We propose that generative memory models, such as those that form the core of our robot memory system, can provide a solution to the symbol grounding problem in embodied artificial intelligence. This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.

Are friends electric? The benefits and risks of human-robot relationships

“…Cognitive architectures have also been devised that store memories of past events (e.g. Dominey et al., 2017 ; Prescott et al., 2019 ) and that construct models of others' actions, beliefs, desires, and intentions (e.g. Scassellati, 2002 ; Johnson and Demiris, 2005 ; Trafton et al., 2013 ; Devin and Alami, 2016 ; Moulin-Frier et al., 2018 ), thus providing some of the cognitive capacities, such as autobiographical memory and “theory of mind,” that underpin human social cognition.…”

Robots as Mirrors of the Human Mind

“…Robots can also constitute means for understanding human cognition and human cognitive development (Asada et al, 2009) by serving as embodied models of the cognitive mechanisms, or in other words, “understanding through building” (see Verschure & Prescott, 2018, for more detailed argument). In this vein, Prescott and colleagues (2019) implemented a multimodal memory system on the iCub robot that was grounded in theories and models from cognitive psychology and neuroscience and showed that the model allows better social functioning of the robot.…”

Abstract Concept Learning in Cognitive Robots

“…As an example of the second category, Prescott et al [40] included emotional signals in a neuroscience-inspired multimodal computational architecture for the autobiographical memory system, named the Mental Time Travel Model (MTTM), implemented to control the iCub robot. The MTTM allows for retrieving past events, including the related emotional associations, and their projection into an imagined future by using the same system.…”