Embodied Artificial Intelligence through Distributed Adaptive Control: An Integrated Framework

TL;DR

This paper advocates for an integrated, embodied approach to AI, emphasizing the importance of combining diverse AI methods within physical, realistic environments to advance cognitive capabilities.

Contribution

It introduces a unified embodied cognitive architecture that synthesizes various AI sub-fields and proposes ecologically-valid benchmarks for complex skill acquisition.

Findings

Unified framework expresses major AI contributions

Embodied agents can develop complex skills in realistic environments

Benchmarking should mimic ecological conditions

Abstract

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.