An Artificial Consciousness Model and its relations with Philosophy of Mind
Eduardo C. Garrido-Merchán, Martin Molina, Francisco M. Mendoza
arXiv Preprint Archive November 30, 2020 via arXiv
Summary
AI-generated from the abstractAn autonomous agent can benefit from a cognitive architecture inspired by conscious beings, using a global workspace that integrates information from subsystems like attention, memory, and inner feelings. In a large experiment set, agents with this architecture navigated environments with multiple independent magnitudes, adapting to find positions matching their preferences. The model incorporates mechanisms for selecting which magnitude to attend to, storing beliefs and past experiences, and controlling information flow. Results suggest that such a design improves the agent's ability to adapt and perform in complex environments.
Study at a glance
| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Keywords | Cs.ai Artificial-consciousness Cognitive-architecture Autonomous-systems Machine-learning |
| Key finding | An autonomous agent with a global workspace cognitive architecture can effectively navigate and adapt in complex environments by integrating attention, memory, and inner preferences. |
Abstract
This work seeks to study the beneficial properties that an autonomous agent can obtain by implementing a cognitive architecture similar to the one of conscious beings. Along this document, a conscious model of autonomous agent based in a global workspace architecture is presented. We describe how this agent is viewed from different perspectives of philosophy of mind, being inspired by their ideas. The goal of this model is to create autonomous agents able to navigate within an environment composed of multiple independent magnitudes, adapting to its surroundings in order to find the best possible position in base of its inner preferences. The purpose of the model is to test the effectiveness of many cognitive mechanisms that are incorporated, such as an attention mechanism for magnitude selection, pos-session of inner feelings and preferences, usage of a memory system to storage beliefs and past experiences, and incorporating a global workspace which controls and integrates information processed by all the subsystem of the model. We show in a large experiment set how an autonomous agent can benefit from having a cognitive architecture such as the one described.