Rives

About Rives​

Rives is a Cartesi App-chain that at it´s core has a gameplay validation primitive. At the core of Rives there is a deterministic fantasy console emulator, called RIV. RIV is built on top of the Cartesi Machine and executes both on the browser on top of web assembly when users are playing a game and inside the Rives app-chain validators. In that way, the computation performed by users is deterministic and can be verified without the developers needing to take any special care for their games to be deterministic. RIV has an API for game developers to use on their games allowing to play sounds, capture user input and draw on the screen among other things. The API documentation is available at https://docs.rives.io . On top of the core validation primitive, Rives has other functionalities like the tapes (replays of the gameplay) and contests (time constrained tournaments with specific rules for a game). As the validation of Rives computations are very demanding, we use an architecture we call inception optimistic rollups to scale the processing capability. Basically every validation of gameplay is an optimistic computation that has it´s result published on the Rives app-chain when final. To scale the read-only part, we have a cache mechanism to serve static assets and dynamic ones that are fetched through inspects. Additionally we have created a "reader node" based on nonodo that serves inspects based on the current externalized state of Rives, which can scale horizontally inspect requests. You can join Rives Discord to talk to the team and clear any technical doubts.

What's next​

We are progressively building more features for all the different user groups in game communities: players, pro-players, fans, streamers, game developers, etc to make all the people involved on a game community share the value generated by it and create virtuous cycles around the community. Rives is spearheading solving multiple novel technical problems for Cartesi Rollups and working close to the core team to create solutions that benefit the entire ecosystem, making Cartesi DApps easier to develop, maintain and more stable/scalable.

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