Embodied Artificial Intelligence through Distributed Adaptive Control: An Integrated Framework

In this paper, we argue that the future of Artificial Intelligence research resides in two keywords: integration and embodiment. We support this claim by analyzing the recent advances of the field. Regarding integration, we note that the most impactful recent contributions have been made possible through the integration of recent Machine Learning methods (based in particular on Deep Learning and Recurrent Neural Networks) with more traditional ones (e.g. Monte-Carlo tree search, goal babbling exploration or addressable memory systems). Regarding embodiment, we note that the traditional benchmark tasks (e.g. visual classification or board games) are becoming obsolete as state-of-the-art learning algorithms approach or even surpass human performance in most of them, having recently encouraged the development of first-person 3D game platforms embedding realistic physics. Building upon this analysis, we first propose an embodied cognitive architecture integrating heterogenous sub-fields of Artificial Intelligence into a unified framework. We demonstrate the utility of our approach by showing how major contributions of the field can be expressed within the proposed framework. We then claim that benchmarking environments need to reproduce ecologically-valid conditions for bootstrapping the acquisition of increasingly complex cognitive skills through the concept of a cognitive arms race between embodied agents.Comment: Updated version of the paper accepted to the ICDL-Epirob 2017 conference (Lisbon, Portugal

Measuring the Additive Effects of Multimedia Social Cue Principles on Learners’ Cognitive Load, Emotions, Attitude, and Learning Outcomes

Multimedia principles are developed and employed to design effective multimedia instructions that foster learning. Specifically, multimedia principles such as personalization, voice, and embodiment principles are developed based on social cues to promote deep learning. Most researchers in the past have investigated the individual effects of these principles on learning. The goal of the present study was to investigate the additive effects of these abovementioned principles on learners’ perceived cognitive load, emotions, attitude, and learning outcomes (i.e. retention and transfer of knowledge). Sixty college students participated in this study. Participants were asked to complete two short instructional modules and a short learning assessment after each module. Additionally, they were asked to complete a NASA Task Load Index (TLX) questionnaire, emotion assessment, and attitude questionnaire. The results suggested that non-personalized instructions lead to higher cognitive load than the personalized instructions. Participants in the personalized voice with embodiment condition had the least feelings of disgust when learning the information and had highest retention scores. Additionally, personalized voice narrations were found to be detrimental for learning. However, if personalized voice narrations are used for instructional purposes, then it must be accompanied with an embodiment to foster learning and improve performance on transfer of knowledge. The findings of this study could be used to improve the design of the multimedia instructions that are effective in fostering learning

‘In the game’? Embodied subjectivity in gaming environments

Human-computer interactions are increasingly using more (or all) of the body as a control device. We identify a convergence between everyday bodily actions and activity within digital environments, and a trend towards incorporating natural or mimetic form of movement into gaming devices. We go on to reflect on the nature of player ‘embodiment’ in digital gaming environments by applying insights from the phenomenology of Maurice Merleau-Ponty. Three conditions for digital embodiment are proposed, with implications for Calleja’s (2011) Player Involvement Model (PIM) of gaming discussed

Six challenges for embodiment research

20 years after Barsalou's seminal perceptual symbols paper (Barsalou, 1999), embodied cognition, the notion that cognition involves simulations of sensory, motor, or affective states, has moved in status from an outlandish proposal advanced by a fringe movement in psychology to a mainstream position adopted by large numbers of researchers in the psychological and cognitive (neuro)sciences. While it has generated highly productive work in the cognitive sciences as a whole, it had a particularly strong impact on research into language comprehension. The view of a mental lexicon based on symbolic word representations, which are arbitrarily linked to sensory aspects of their referents, for example, was generally accepted since the cognitive revolution in the 1950s. This has radically changed. Given the current status of embodiment as a main theory of cognition, it is somewhat surprising that a close look at the state of the affairs in the literature reveals that the debate about the nature of the processes involved in language comprehension is far from settled and key questions remain unanswered. We present several suggestions for a productive way forward