Emmanuella Edem-Dartey

Project Owner

Motivation-as-a-Service(MaaS) for AGI Agents

Expert Rating

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Type SingularityNET RFP
Funding Request $20,000 USD
RFP Guidelines Develop a framework for AGI motivation systems

Overview

AGI frameworks lack reusable motivation systems, forcing developers to hardcode drives. MaaS solves this with an API-driven service allowing agents to externally manage motivational states (drives, goals, feedback). By decoupling motivation logic, developers test novel utility models (e.g., “alien” drives), reuse architectures, and improve decision transparency. Deliverables: REST API, MeTTA/Python clients, Docker deployment, and configurable templates. Accelerates AGI experimentation and multi-agent ecosystems. Open-source under Apache 2.0.

Project Tags:
Community and Collaboration

RFP Guidelines

Develop a framework for AGI motivation systems

Complete & Awarded

Type SingularityNET RFP
Total RFP Funding $40,000 USD
Proposals 19
Awarded Projects 2

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

Our Team

Led by Emmanuella Edem-Dartey, our team combines expertise in API, AGI, docs, and ethics.

- 3 backend engineers (Python, FastAPI, Node.js)
- 2 AGI specialists (MeTTA/PRIMUS)
- 2 technical writers (AI explainability)
- 1 PhD ethics advisor (value-alignment)

Company Name (if applicable)

Catalyst Trail

Project details

*Problem Statement:

Current AGI agents in frameworks like OpenCog Hyperon and PRIMUS rely on rigid, hardcoded motivation systems. This forces developers to rebuild drives (e.g., curiosity, energy preservation) for each agent, stifling experimentation and reuse. Siloed systems also obscure decision-making logic, hindering transparency and ethical oversight.

*Solution Overview:

MaaS decouples motivation logic into a standalone service. Key components:

- RESTful API: Agents query endpoints like `/compute-priority` to resolve motivational conflicts.

- Dynamic Drive Engine: YAML/JSON templates define drives (novelty, homeostasis) with adjustable weights and decay rates.

- Feedback Integration: Agents submit environmental feedback (e.g., task success) to dynamically update drive states.

- Multi-Agent Support: Shared or competitive motivational profiles enable swarm behaviors.

*Use Cases:

- A PRIMUS agent offloads curiosity vs. conservation priority calculations to MaaS.

- Developers hot-swap "alien" drives (e.g., entropy-maximizing) without rewriting agent code.

- Researchers audit agent decisions via transparent priority scores.

Open Source Licensing

Apache License

Background & Experience

Emmanuella Edem-Dartey: Architect of OpenCog’s motivational subsystem (2021), co‑author of three peer‑reviewed papers on modular AGI design, and speaker at AGI-2023 on decoupled motivation services.

Backend Team: Developed “Emotion‑as‑a‑Service,” an API for chatbot affect modeling (GitHub repo: 500+ stars, 50+ forks); led deployment on AWS and GCP with 99.9% uptime. Engineered high-throughput REST platforms handling 1k+ concurrent clients.

PRIMUS/MeTTA Contributors: Created the MeTTA‑Hyperon bridge enabling seamless cross‑framework agent messaging; maintainers of MeTTA SDK with 1k+ downloads/month.

Ethical Utility Project: Collaborated on Deep Funding’s “Ethical Utility Functions for AGI” (Q3 2023), producing open‑source libraries and ethical guidelines adopted by two research consortia.

Community Engagement: Hosted three workshops on motivation-driven agent design; published articles in Medium and arXiv on drive modulators and transparency.

Activity Summary

Milestones

4

Total

Discussion

0

Total Comments

Reviews

0

Total Posted

Project Team

1

Total People

Total Milestones
4
Total Budget
$20,000_USD
Last Updated
20 May 2025

Milestone 1 - Core API + Basic Drives

Description

Develop REST API (FastAPI) with endpoints for drive management including `/drives` `/feedback` and `/compute-priority`. Implement YAML-based configuration supporting curiosity (novelty-seeking) and homeostasis (energy preservation) drives. Build Docker image for local testing.

Deliverables

Functional API server Docker image 2 drive templates (curiosity homeostasis) unit tests.

Budget

$7,000 USD

Success Criterion

API handles 100+ concurrent agents; demo agent selects actions via priority scores.

Milestone 2 - Agent Integration

Description

Develop MeTTA/Python client libraries with async API support. Create 2 demo agents: Explorer (prioritizes novelty) and Conservator (prioritizes resource retention). Record tutorial video showing real-time drive adjustments.

Deliverables

Client libraries 3 demo agents tutorial video load-test scripts.

Budget

$3,000 USD

Success Criterion

Agents autonomously adjust behavior; 90% API uptime under 50-agent load.

Milestone 3 - Dynamic Motivation Tuning

Description

Implement feedback-driven weight adjustment and stress-test with 10+ agents. Develop analytics dashboard to visualize drive state changes.

Deliverables

Feedback engine dashboard load-test report 5+ test cases.

Budget

$7,000 USD

Success Criterion

Drives adapt ±20% weights post-feedback; <1s API latency.

Milestone 4 - Launch Ready

Description

Finalize OpenAPI docs deployment guides and 3 tutorials. Publish DockerHub image and GitHub repo.

Deliverables

Public GitHub repo DockerHub image whitepaper 3 tutorials.

Budget

$3,000 USD

Success Criterion

500+ documentation pageviews in first month; community feedback incorporated.

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The weighted average of the 4 perspectives Overall

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Each RFP defines a maximum allowed budget, but teams can differentiate their proposal by offering a solution with a lower budget or a wider scope.Value for money

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This rating indicates compliance to 'Must haves' but also adaptation of 'Nice to haves' and Non-functional requirements defined in the RFP.Compliance with RFP requirements

0.0
RFPs will offer varying degrees of freedom. This rating indicates the quality of the team's specific solution ideas, the provided details, and the reviewer's confidence in the team's ability to execute.Solution details and team expertise

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