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Overview

When building a Solver, you can register actions to the MAOTO Marketplace. These actions define specific capabilities that a Solver can execute when handling tasks.

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Required Parameters for an Action

Each action must include the following attributes:

  1. name

    • The name of the action. (TODO: must be unique?)

  2. parameters

    • Defines the input parameters required for the action to be executed.
    • If required parameters are missing, the Solver can initiate an Information Request to request additional details from the Provider.

  3. description

    • A clear explanation of what the action does.

  4. tags

    • Keywords used by MAOTO to shortlist actions with relevant tasks. More information on tags can be found in the Subscription documentation.

  5. cost

    • The estimated cost to execute the action.

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Dynamic Parameters & Cost Adjustments

All action parameters can be dynamically set by the Solver, making them adaptable to the task at hand.

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Cost Dynamics

The cost of an action is not fixed and can be adjusted based on multiple factors:

  • Task complexity – More complex tasks may require additional computation or processing.
  • Execution time – Longer tasks may have higher costs.
  • Resource utilization – If an action requires external API calls, processing power, or paid services, costs may increase.

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Example: Ride Hailer Solver

In a ride-hailing scenario, the cost of an action (e.g., booking a ride) is highly case-specific.

  • Factors such as distance, traffic conditions, surge pricing, and availability of drivers dynamically affect the cost.
  • The Solver adapts pricing in real-time before placing a bid.
  • Different ride-hailing providers (e.g., Uber, Lyft, etc.) may have different pricing structures, which the Solver can factor in before setting its final bid.

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Scenario: Price Variation Based on External Factors

For instance, the price of a ride from Point A to Point B may vary due to:

  • Time of day – Peak hours may lead to surge pricing.
  • Traffic conditions – Higher congestion can increase trip time and costs.
  • Availability of drivers – Fewer drivers lead to higher demand-based pricing.

The Solver can analyze these variables and dynamically adjust the bid price to ensure competitiveness and profit.

​
Completion Criteria

TODO: Add content

​
Overview

When building a Solver, you can register actions to the MAOTO Marketplace. These actions define specific capabilities that a Solver can execute when handling tasks.

​
Required Parameters for an Action

Each action must include the following attributes:

  1. name

    • The name of the action. (TODO: must be unique?)

  2. parameters

    • Defines the input parameters required for the action to be executed.
    • If required parameters are missing, the Solver can initiate an Information Request to request additional details from the Provider.

  3. description

    • A clear explanation of what the action does.

  4. tags

    • Keywords used by MAOTO to shortlist actions with relevant tasks. More information on tags can be found in the Subscription documentation.

  5. cost

    • The estimated cost to execute the action.

​
Dynamic Parameters & Cost Adjustments

All action parameters can be dynamically set by the Solver, making them adaptable to the task at hand.

​
Cost Dynamics

The cost of an action is not fixed and can be adjusted based on multiple factors:

  • Task complexity – More complex tasks may require additional computation or processing.
  • Execution time – Longer tasks may have higher costs.
  • Resource utilization – If an action requires external API calls, processing power, or paid services, costs may increase.

​
Example: Ride Hailer Solver

In a ride-hailing scenario, the cost of an action (e.g., booking a ride) is highly case-specific.

  • Factors such as distance, traffic conditions, surge pricing, and availability of drivers dynamically affect the cost.
  • The Solver adapts pricing in real-time before placing a bid.
  • Different ride-hailing providers (e.g., Uber, Lyft, etc.) may have different pricing structures, which the Solver can factor in before setting its final bid.

​
Scenario: Price Variation Based on External Factors

For instance, the price of a ride from Point A to Point B may vary due to:

  • Time of day – Peak hours may lead to surge pricing.
  • Traffic conditions – Higher congestion can increase trip time and costs.
  • Availability of drivers – Fewer drivers lead to higher demand-based pricing.

The Solver can analyze these variables and dynamically adjust the bid price to ensure competitiveness and profit.

​
Completion Criteria

TODO: Add content