Interpretation of Daydreams Protocol: Unleash the unlimited potential of AI Agent in full-chain games

Author: lordOfAFew

Translation: MetaCat

☁️Daydreams Protocol

Daydreams has implemented a generative full-chain game AI Agent through cooperation with @ohayo_dojo.

Coming soon:

• @ai16zdao
• @Playgrounds0x
• @0xzerebro
• and any AI Agent framework

In the next month, anyone can deploy AI Agent through Daydreams to play any Dojo-based full-chain game on Starknet.

To me, once this protocol matures, these Agents will be able to do anything, even deploy their own smart contracts. This is all possible thanks to the thought chaining and contextual support provided by Daydreams.

See the POC (proof of concept) in action in @RealmsEternum: (@0xtechnoir)

 Video link: https://x.com/lordOfAFew/status/1871842343575593065

Daydreams provides a blueprint for creating autonomous full-chain game AI Agents. These AI Agents can understand the game status on the chain, use historical data as context, and continuously optimize strategies through an evolving chain of thinking.

We introduced a vector database as a storage medium for long-term memory, and implemented a "group collaboration space" composed of multiple AI Agents to share knowledge and achieve rapid collective self-upgrade.

This is the core mechanism by which AI Agents think and decide how they act.

protocol

The protocol is designed to allow AI agents to construct dynamic queries and actions, rather than relying on the static actions used by most systems today. It does this by providing the context needed to build "thought chains."

We have generalized the architecture so any application developed based on @ohayo_dojo can integrate it with minimal configuration.

Stay tuned for more content.

Why a full-chain game?

The full-chain game environment has its own inherent profit motive, transforming strategies from abstract puzzle solving into economically driven optimization behaviors.

In full-chain games, AI Agents will be directly incentivized to maximize their on-chain profits. This measurable and universal "profit function" prompts the agent to continuously improve itself and gives the learning process a realistic motivation.

In addition, due to the unique incentive mechanism, the architecture of the full-chain game is more adaptable. AI Agents can participate in games without the need for customized APIs, and all existing infrastructure can be used directly.

Why announce now?

Over the past two years, the developers at @cartridge_gg, @ohayo_dojo, and @LootRealms have been building the infrastructure to make this possible. As is our style, this is all open source and we encourage community contributions and discussion.

This is a project in its early stages and our main goal is to showcase these capabilities in @RealmsEternum Season 1 in a few months. If you want to get involved and contribute, now is the time.