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Dynamic E Andy
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Monifix

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Overview

The development of a motivation system for Artificial General Intelligence (AGI) is a foundational challenge in achieving safe, autonomous, and goal-directed machine intelligence. A well-structured motivation framework is essential to guide AGI behavior, ensuring alignment with human values and long-term safety. This document proposes a high-level framework to develop a motivation system that can function as the core of AGI’s decision-making and behavioral architecture. It integrates interdisciplinary insights from cognitive science, neuroscience, machine learning, and ethics. The framework emphasizes modularity, adaptability, and alignment while remaining robust in dynamic environments

RFP Guidelines

Develop a framework for AGI motivation systems

Internal Proposal Review
  • Type SingularityNET RFP
  • Total RFP Funding $40,000 USD
  • Proposals 21
  • Awarded Projects n/a
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SingularityNET
Apr. 14, 2025

Develop a modular and extensible framework for integrating various motivational systems into AGI architectures, supporting both human-like and "alien digital" intelligences. This could be done as a highly detailed and precise specification, or as a relatively simple software prototype with suggestions for generalization and extension. Bids are expected to range from $15,000 - $30,000.

Proposal Description

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  • Total Milestones

    1

  • Total Budget

    $10,009 USD

  • Last Updated

    25 May 2025

Milestone 1 - Launch in a safe, semi-open environment

Description

Conduct Ethical and Alignment Audits Engage external reviewers for ethical testing, misuse analysis, and safety assessment • Deliverable: Ethics and Alignment Audit Report Phase 5: Deployment and Evaluation (Months 17–20) Milestone 5.1: Deploy in Sandbox or Testbed Environment • Launch in a safe, semi-open environment for longitudinal study Measure interaction with human users, long-term consistency, and safety metrics Deliverable: Testbed Deployment and Evaluation Report Milestone 5.2: Public Demonstration and Stakeholder Review Conduct live demo for funding bodies, advisors, and ethical review panels Gather feedback and issue final round of adjustments Deliverable: Demonstration Event and Final System Review Phase 6: Documentation and Dissemination (Months 21–24) Milestone 6.1: Final Documentation and Reporting Deliver complete technical documentation, user manuals, and system API specs Compile results and publish final report Deliverable: Comprehensive Project Documentation Package Milestone 6.2: Research Publication and Open Knowledge Sharing Prepare academic papers and presentations for relevant AI, cognitive science, and ethics conferences

Deliverables

Ethics & Alignment Audit Report Description: An independent evaluation report conducted by external reviewers. Includes safety verification, misuse risk assessment, ethical compliance, and recommendations. Purpose: Validate the system’s alignment, trustworthiness, and responsible design. Testbed Deployment and Evaluation Report Description: Summary of performance in a controlled, semi-open environment with real-time user interaction. Includes feedback metrics, failure cases, and response patterns. Purpose: Assess real-world readiness and user compatibility. Final System Demonstration Description: A live or recorded showcase of the AGI system functioning in diverse scenarios, presented to stakeholders, advisors, and reviewers. Purpose: Demonstrate project outcomes and readiness for further development or integration. Technical Documentation Package Description: Comprehensive technical documents including system architecture, API specs, deployment instructions, test cases, and maintenance guidelines. Purpose: Support future development, collaboration, and reproducibility Academic Publications and Open Knowledge Release Description: Peer-reviewed papers, conference presentations, and (optionally) open-source components or datasets. Purpose: Contribute to the scientific community and support ethical plan.

Budget

$10,009 USD

Success Criterion

Adaptability and Learning Continual Learning The AGI refines its motivation and goal-selection processes over time without catastrophic forgetting. Success Indicator: Retains and improves goal performance across multiple learning episodes with <5% degradation in older task domains. Cross-Domain Transfer The motivation system adapts to new domains without requiring full reprogramming. Success Indicator: Demonstrates effective goal pursuit in at least 3 novel environments with only minor retraining. Transparency and Interpretability Motivation Explainability The AGI provides human-readable explanations of why it chose specific goals or actions. Success Indicator: 80% user understanding score in explainability testing (e.g., via surveys or usability studies). Monitoring Interface Effectiveness Safety and interpretability dashboards successfully track, visualize, and allow control of AGI motivational state. Success Indicator: Interface supports real-time updates and error-free logging across 95% of test sessions. Deployment and Demonstration Readiness Simulation Evaluation Completion The AGI passes comprehensive simulation tests under varied goal conflicts, reward sparsity, and ethical dilemmas. Success Indicator: Passes all defined benchmark tests and edge cases in simulation scenarios. Stakeholder Demonstration The final system can be demonstrated in a live or sandbox environment to stakeholders with minimal risk and maximum transparency.

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