PhilipeSantos

Project Owner

Procedurally Generated Interactive Experience

Type SingularityNET RFP
Funding Awarded $15,000 USD
RFP Guidelines Develop interesting demos in MeTTa

Status

Overall Status
⏳ Contract Pending
Funding Transfered
$0_USD
Max Funding Amount
$15,000_USD

Funding Schedule

View Milestones

Milestone Release 1	$1,875 USD	Pending	TBD
Milestone Release 2	$1,875 USD	Pending	TBD
Milestone Release 3	$1,875 USD	Pending	TBD
Milestone Release 4	$1,875 USD	Pending	TBD
Milestone Release 5	$1,875 USD	Pending	TBD
Milestone Release 6	$1,875 USD	Pending	TBD
Milestone Release 7	$1,875 USD	Pending	TBD
Milestone Release 8	$1,875 USD	Pending	TBD

Overview

This proposal aims to develop an innovative interactive experience powered by MeTTa/Hyperon, highlighting their advanced reasoning and memory management capabilities. Users will engage with a dynamic system where their actions drive the progression, while a live panel provides insight into the underlying logic in real time. The project balances entertainment with education, offering a clear demonstration of MeTTa/Hyperon's potential. Future enhancements may include integration with Zarqa’s capabilities to further expand the system’s interactivity and depth.

RFP Guidelines

Develop interesting demos in MeTTa

Complete & Awarded

Type SingularityNET RFP
Total RFP Funding $100,000 USD
Proposals 21
Awarded Projects 4

SingularityNET

Aug. 12, 2024

Create educational and/or useful demos using SingularityNET's own MeTTa programming language. This RFP aims at bringing more community adoption of MeTTa and engagement within our ecosystem, and to demonstrate and expand the utility of MeTTa. Researchers must maintain demos for a minimum of one year.

Proposal Description

Project details

Project Summary:

This proposal outlines the creation of a web-based RPG Text Game powered by MeTTa/Hyperon for its core logic, reasoning, and memory capabilities. The game generates unique worlds on demand, where players navigate procedurally created maps, interact with enemies and puzzles, and manage their inventory to progress. The player's success is measured using a score system that evaluates their performance throughout the game.

Players interact with the game through a modular system where they can type actions from a predefined pool. This approach ensures clarity while maintaining flexibility for future expansions. A live side panel will display the MeTTa code in action, providing educational insight into the logic and memory systems driving the game.

Core Objectives:

Engage Players: Provide a flexible and challenging experience where users can generate new game worlds and strive for a high score.
Showcase MeTTa/Hyperon: Demonstrate these technologies' power to handle reasoning, procedural generation, and memory in an interactive and visually transparent manner.
Encourage Replayability: Allow users to generate unique stories whenever they want, ensuring long-term engagement.

Game Features:

Web Interface:

Input Panel: Players interact with the game by typing actions from a modular pool (e.g., "move to forest," "use potion").
Output Panel: Displays the narrative and updates based on user choices.
Code Panel: A live-updating side panel shows the MeTTa/Hyperon code in action, providing transparency into the game's logic and memory systems.

Procedural Generation:

On-demand generation of unique worlds using MeTTa, including:

Maps: Randomized locations with logical connections and obstacles.
Enemies: Opponents with varied behaviors and challenges.
Items: Tools for solving puzzles and unlocking areas.
Puzzles: Logical challenges requiring reasoning to solve.

All generation logic and memory management will be handled by MeTTa/Hyperon.

Exploration System:

Players navigate a procedurally generated map, discovering items, defeating enemies, and solving puzzles.
Modular interaction ensures clarity and ease of use.

Inventory Management:

Players collect and use items strategically to progress through the game, such as unlocking doors, defeating enemies, or bypassing obstacles.

Score System:

Player performance is measured through a scoring system based on their choices and actions during the game.

Educational Transparency:

The code panel displays real-time updates of MeTTa/Hyperon logic and memory, showcasing:

How the game state evolves with player actions.
How memory capabilities track progress, player inventory, and explored areas.
The reasoning behind enemy behaviors and puzzle solutions.

Technical Implementation

Core System:

Built entirely using MeTTa/Hyperon, including:

Procedural generation logic for maps, puzzles, and challenges.
Memory capabilities to track player actions, inventory, and game state.
Game state reasoning to ensure logical consistency and dynamic responses.

Frontend:

Developed using React.js for a modern, responsive user interface.
Three primary panels:

Interaction Panel: Modular action selection and narrative output.
MeTTa/Hyperon Code Panel: Live updates of reasoning and memory operations.
Summary Panel: Displays the player’s score and performance analysis upon completion.

Procedural Logic:

Map generation: Logical placement of locations, enemies, and items.
Puzzle creation: Procedurally generated challenges based on predefined templates.
Enemy behaviors: Logical AI governing interactions and conflicts.
Player progress and inventory.
Puzzle states and solved challenges.

Documentation:

User Guide: Instructions for playing the game and understanding the interface.
Developer Documentation: Explanation of how MeTTa/Hyperon powers the game logic, procedural generation, and memory management.
Educational Material: Tutorials on reasoning systems and memory management.

Future Applications:

Integration with Zarqa:

Enable natural language input for user actions.
Expand the narrative depth with AI-generated storytelling for a richer gaming experience.

Conclusion:

This project demonstrates how MeTTa/Hyperon can power a procedurally generated RPG that is engaging, challenging, and educational. By focusing on logical reasoning, modular interaction, and memory management, it highlights the strengths of these systems in a highly interactive and visually transparent format. Players are encouraged to explore and solve puzzles strategically, with the ability to generate a new adventure whenever they wish.

Open Source Licensing

Apache License

Activity Summary

Milestones

8

Total

Discussion

0

Total Comments

Reviews

4

Total Posted

Project Team

1

Total People

Group Expert Rating (Final)

Overall

5.0

Compliance with RFP requirements 4.3
Solution details and team expertise 4.3
Value for money 3.7

New reviews and ratings are disabled for Awarded Projects

Overall Community

4.3

from 4 reviews

5

1
4

2
3

0
2

0
1

0

Feasibility

4.3

from 4 reviews

Viability

4.3

from 4 reviews

Desirabilty

3.7

from 4 reviews

Usefulness

0

from 4 reviews

Sort by

4 ratings

Expert Review 1
Overall

4.0
- Compliance with RFP requirements 4.0
- Solution details and team expertise 4.0
- Value for money 0.0
Application of MeTTa to core mechanics lacks clarity

Creative proposal. Highlights reasoning, memory, and procedural logic with a live MeTTa code panel for transparency. Application of MeTTa to core mechanics lacks clarity, particularly in procedural generation and reasoning. Developer has strong technical experience but no demonstrated MeTTa/Hyperon expertise. Promising project but needs clearer alignment.

Expert Review 2
Overall

4.0
- Compliance with RFP requirements 4.0
- Solution details and team expertise 3.0
- Value for money 0.0

Expert Review 3
Overall

5.0
- Compliance with RFP requirements 5.0
- Solution details and team expertise 4.0
- Value for money 0.0
this would be a simple, fun, educational demo to have ... and potentially could serve as a prototype to spur development of more serious game-AI uses of MeTTA/Hyperon

Posting publicaly as

edit profile

Overall

Confidence level that the project is possible at all Feasibility

0
Confidence in a successful outcome considering team, time, and budget Viability

0
Market fit - Balancing needs and benefits against competition Desirabilty

0
To what extent will the project help the AI platform grow? Usefulness

0

Review Headline

0 /50 chars

Review Summary

0 /5000 chars

Expert Review

Overall

Confidence level that the project is possible at all Feasibility

0
Confidence in a successful outcome considering team, time, and budget Viability

0
Market fit - Balancing needs and benefits against competition Desirabilty

0
To what extent will the project help the AI platform grow? Usefulness

0

Review Headline

0 /50 chars

Review Summary

0 /5000 chars

Reviews and Ratings in Deep Funding are structured in 4 categories. This will ensure that the reviewer takes all these perspectives into account in their assessment and it will make it easier to compare different projects on their strengths and weaknesses. Overall (Primary) This is an average of the 4 perspectives. At the start of this new process, we are assigning an equal weight to all categories, but over time we might change this and make some categories more important than others in the overall score. (This may even be done retroactively). Feasibility (secondary) This represents the user's assessment of whether the proposed project is theoretically possible and if it is deemed feasible. E.g. A proposal for nuclear fission might be theoretically possible, but it doesn’t look very feasible in the context of Deep Funding. Viability (secondary) This category is somewhat similar to Feasibility, but it interprets the feasibility against factors such as the size and experience of the team, the budget requested, and the estimated timelines. We could frame this as: “What is your level of confidence that this team will be able to complete this project and its milestones in a reasonable time, and successfully deploy it?” Examples:

A proposal that promises the development of a personal assistant that outperforms existing solutions might be feasible, but if there is no AI expertise in the team the viability rating might be low.
A proposal that promises a new Carbon Emission Compensation scheme might be technically feasible, but the viability could be estimated low due to challenges around market penetration and widespread adoption.

Desirability (secondary) Even if the project team succeeds in creating a product, there is the question of market fit. Is this a project that fulfills an actual need? Is there a lot of competition already? Are the USPs of the project sufficient to make a difference? Example:

Creating a translation service from, say Spanish to English might be possible, but it's questionable if such a service would be able to get a significant share of the market

Usefulness (secondary) This is a crucial category that aligns with the main goal of the Deep Funding program. The question to be asked here is: “To what extent will this proposal help to grow the Decentralized AI Platform?” For proposals that develop or utilize an AI service on the platform, the question could be “How many API calls do we expect it to generate” (and how important / high-valued are these calls?). For a marketing proposal, the question could be “How large and well-aligned is the target audience?” Another question is related to how the budget is spent. Are the funds mainly used for value creation for the platform or on other things? Examples:

A metaverse project that spends 95% of its budget on the development of the game and only 5 % on the development of an AI service for the platform might expect a low ‘usefulness’ rating here.

A marketing proposal that creates t-shirts for a local high school, would get a lower ‘usefulness’ rating than a marketing proposal that has a viable plan for targeting highly esteemed universities in a scaleable way.
An AI service that is fully dedicated to a single product, does not take advantage of the purpose of the platform. When the same service would be offered and useful for other parties, this should increase the ‘usefulness’ rating.

Reviews and Ratings in Deep Funding are structured in 4 categories. This will ensure that the reviewer takes all these perspectives into account in their assessment and it will make it easier to compare different projects on their strengths and weaknesses. Overall (Primary) This is an average of the 4 perspectives. At the start of this new process, we are assigning an equal weight to all categories, but over time we might change this and make some categories more important than others in the overall score. (This may even be done retroactively). Feasibility (secondary) This represents the user\'s assessment of whether the proposed project is theoretically possible and if it is deemed feasible. E.g. A proposal for nuclear fission might be theoretically possible, but it doesn’t look very feasible in the context of Deep Funding. Viability (secondary) This category is somewhat similar to Feasibility, but it interprets the feasibility against factors such as the size and experience of the team, the budget requested, and the estimated timelines. We could frame this as: “What is your level of confidence that this team will be able to complete this project and its milestones in a reasonable time, and successfully deploy it?” Examples:

A proposal that promises the development of a personal assistant that outperforms existing solutions might be feasible, but if there is no AI expertise in the team the viability rating might be low.
A proposal that promises a new Carbon Emission Compensation scheme might be technically feasible, but the viability could be estimated low due to challenges around market penetration and widespread adoption.

Creating a translation service from, say Spanish to English might be possible, but it\'s questionable if such a service would be able to get a significant share of the market

A metaverse project that spends 95% of its budget on the development of the game and only 5 % on the development of an AI service for the platform might expect a low ‘usefulness’ rating here.

A marketing proposal that creates t-shirts for a local high school, would get a lower ‘usefulness’ rating than a marketing proposal that has a viable plan for targeting highly esteemed universities in a scaleable way.
An AI service that is fully dedicated to a single product, does not take advantage of the purpose of the platform. When the same service would be offered and useful for other parties, this should increase the ‘usefulness’ rating.

Total Milestones
8
Total Budget
$15,000_USD
Last Updated
3 Feb 2025

Join the Discussion (0)

Expert Ratings

Reviews & Ratings

Group Expert Rating (Final)

Overall

5.0

Compliance with RFP requirements 4.3
Solution details and team expertise 4.3
Value for money 3.7

New reviews and ratings are disabled for Awarded Projects

Expert Review 1
Overall

4.0
- Compliance with RFP requirements 4.0
- Solution details and team expertise 4.0
- Value for money 0.0
Application of MeTTa to core mechanics lacks clarity

Creative proposal. Highlights reasoning, memory, and procedural logic with a live MeTTa code panel for transparency. Application of MeTTa to core mechanics lacks clarity, particularly in procedural generation and reasoning. Developer has strong technical experience but no demonstrated MeTTa/Hyperon expertise. Promising project but needs clearer alignment.

Expert Review 2
Overall

4.0
- Compliance with RFP requirements 4.0
- Solution details and team expertise 3.0
- Value for money 0.0

Expert Review 3
Overall

5.0
- Compliance with RFP requirements 5.0
- Solution details and team expertise 4.0
- Value for money 0.0
this would be a simple, fun, educational demo to have ... and potentially could serve as a prototype to spur development of more serious game-AI uses of MeTTA/Hyperon

The weighted average of the 4 perspectives Overall

0.0
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

0.0
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

0.0

Review Headline

0 /50 chars

Review Summary

0 /5000 chars

The weighted average of the 4 perspectives Overall

5.0
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

3.7
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

4.3
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

4.3

Review Headline

0 /50 chars

0 /5000 chars

Warning: Adding final group rating for this project will prevent expert users from adding new or editing existing reviews

Reviews and Ratings in Deep Funding are structured in 4 categories. This will ensure that the reviewer takes all these perspectives into account in their assessment and it will make it easier to compare different projects on their strengths and weaknesses. Overall (Primary) This is an average of the 4 perspectives. At the start of this new process, we are assigning an equal weight to all categories, but over time we might change this and make some categories more important than others in the overall score. (This may even be done retroactively). Feasibility (secondary) This represents the user\'s assessment of whether the proposed project is theoretically possible and if it is deemed feasible. E.g. A proposal for nuclear fission might be theoretically possible, but it doesn’t look very feasible in the context of Deep Funding. Viability (secondary) This category is somewhat similar to Feasibility, but it interprets the feasibility against factors such as the size and experience of the team, the budget requested, and the estimated timelines. We could frame this as: “What is your level of confidence that this team will be able to complete this project and its milestones in a reasonable time, and successfully deploy it?” Examples:

A proposal that promises the development of a personal assistant that outperforms existing solutions might be feasible, but if there is no AI expertise in the team the viability rating might be low.
A proposal that promises a new Carbon Emission Compensation scheme might be technically feasible, but the viability could be estimated low due to challenges around market penetration and widespread adoption.

Creating a translation service from, say Spanish to English might be possible, but it\'s questionable if such a service would be able to get a significant share of the market

A metaverse project that spends 95% of its budget on the development of the game and only 5 % on the development of an AI service for the platform might expect a low ‘usefulness’ rating here.

A marketing proposal that creates t-shirts for a local high school, would get a lower ‘usefulness’ rating than a marketing proposal that has a viable plan for targeting highly esteemed universities in a scaleable way.
An AI service that is fully dedicated to a single product, does not take advantage of the purpose of the platform. When the same service would be offered and useful for other parties, this should increase the ‘usefulness’ rating.

PhilipeSantos

Project Owner

I will manage all aspects of the project, including backend and frontend development, game design, and project execution, along with comprehensive testing, optimization, and detailed documentation.

View Profile