> For the complete documentation index, see [llms.txt](https://docs.essential.builders/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.essential.builders/learn/declarative-blockchains/what-is-a-declarative-blockchain/criterion-1-constraints-on-state.md).

# Criterion 1: Constraints on State

Because early intent projects output transactions to be settled via imperative execution, they conceive of intents as *constraints on state transitions*. **In declarative blockchains like Essential, intents exist not as *****constraints on the state transition function*****, but as *****constraints on state itself*****.**

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Leveraging **constraints on state** is a critical property of declarative blockchains, as it allows developers and users to “constrain” the solution space of acceptable (and optimal) outcomes.
{% endhint %}

## Constraint Programming

To enable the enforcement of constraints on state, Essential’s architecture is based on[ constraint programming](https://en.wikipedia.org/wiki/Constraint_programming?ref=blog.essential.builders), a subset of the declarative programming paradigm.

Constraint programming is an extremely ergonomic approach to expressing and enforcing outcomes within state machines, and is especially useful for solving large-scale combinatorial problems—for example, finding a series of optimal state transitions among a complex on-chain solution space (i.e. solving intents).

When a user submits an intent, they are declaratively outlining a set of variables as well as constraints on those variables, narrowing down the space of feasible solutions.

## Constraint Optimization: Maximizing Utility

The constraint-based model also enables users to specify an objective *utility function*, which represents their preferences and preference ordering.

Solvers can then attempt to solve a[ *constraint optimization problem*](https://en.wikipedia.org/wiki/Constrained_optimization?ref=blog.essential.builders), which consists of maximizing the user’s utility (as described in the objective function outlined within the user’s intent). Solvers are not just trying to *satisfy* the user’s intent, but to *maximize* the user's utility with respect to their objective function.

Put more simply, solvers compete to answer the question: *Given state X and objective function F, what new state Y maximizes the user’s satisfaction?* The solution that results in the highest satisfaction can then be identified as the winning solution.

## Constraints on State: Key Takeaway

Because declarative blockchains enable users to directly constrain state, **no state transition may be included if it does not achieve the user’s intended outcome.** Unlike imperative blockchains, there is no risk of state drift causing unintended outcomes or failed transactions.