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Robotic Consciousness Marcros

19 Jan 2025

—layout: post title: “MARCOS and TCAI: Comparing Approaches to Machine Consciousness” description: “Analysis of López De Luise’s MARCOS system for robotic consciousness and its implications for TCAI development in autonomous navigation and decision-making.” keywords: “MARCOS, López De Luise, robotic consciousness, TCAI, autonomous navigation, cognitive architectures” date: 2025-01-19 last_modified_at: 2026-06-30 author: “Zaesar” category: “Research” tags: [ “MARCOS”, “Robotic Consciousness”, “TCAI Development”, “Autonomous Systems”, “Cognitive Architecture”, “Navigation AI”, ] canonical_url: “https://theconsciousness.ai/posts/robotic-consciousness-marcos/” source: “Daniela López De Luise; Nelson Biedma; Lucas Martín Rancez; Leonardo Isoba; David Trejo Pizzo. ‘Robotic Consciousness: Evaluation of a Proposal.’” paper_url: “https://www.academia.edu/11505054/Robotic_consciousness_Evaluation_of_a_proposal” source_inspiration_paper: “Daniela López De Luise; Nelson Biedma; Lucas Martín Rancez; Leonardo Isoba; David Trejo Pizzo. ‘Robotic Consciousness: Evaluation of a Proposal.’” sitemap: false noindex: true —

How can consciousness-inspired frameworks enhance robotic autonomy? This paper by Daniela López De Luise and colleagues introduces MARCOS (Movement of Autonomous Robotics Codelet System), a robotic consciousness model designed to support adaptive indoor navigation and decision-making.

Robotic Consciousness. Evaluation of a Proposal, authored by Daniela López De Luise, Nelson Biedma, Lucas Martín Rancez, Leonardo Isoba, and David Trejo Pizzo, focuses on MARCOS, a system implementing CoFram, a framework inspired by LIDA and global workspace theories, to improve autonomous robot performance.

Key Highlights

  • Consciousness Framework (CoFram) Provides a flexible framework for developing consciousness-inspired robotic models, emphasizing concept learning and adaptation.
  • Dual-Loop Architecture Utilizes a Real-Time Controller (RTC) for immediate decisions and a Robot Task Adviser (RTA) for strategic planning and obstacle navigation.
  • Dynamic Knowledge Base MARCOS learns and updates its internal map, adapting to unknown obstacles and enhancing decision-making capabilities.
  • Codelet Mechanism Employs codelets, specialized agents handling specific tasks, to process concepts and propose strategies dynamically.

Connection to TCAI

The Consciousness AI (TCAI) aligns with this study through:

  • Adaptive Learning TCAI can integrate MARCOS’ dual-loop architecture to enhance adaptability in dynamic environments.
  • Conceptual Frameworks CoFram-inspired methods can inform ACM’s strategy for balancing short- and long-term goals.
  • Agent-Based Modeling The use of codelets complements ACM’s modular design for simulating emergent behaviors.

For a detailed exploration of the MARCOS system and its applications, access the full paper here.

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