System

A system comprising:

• circuitry configured to:
• receive, via a communication interface coupled to a packet-switched network, input data from a terminal apparatus including a target region identifier, an implementation period specification, and an upper expenditure limit value;
• acquire reference data including historical pattern data and trend information from a storage medium;
• construct a parameterized instruction sequence based on the input data and the reference data, and provide the parameterized instruction sequence to a generative neural network model having a transformer-based architecture including a plurality of self-attention layers to generate behavior plan data including activity element data, movement resource data, facility resource data, and cost information data;
• verify the behavior plan data against the upper expenditure limit value and the implementation period specification;
• convert the verified behavior plan data into structured guide data for an electronic medium including time-series scheduling information and cost breakdown information;
• and
• transmit the structured guide data to the terminal apparatus and, upon receiving a batch resource allocation request, execute resource allocation processes with external resource management apparatuses via the packet-switched network.

A method performed by circuitry, the method comprising:

• receiving input data from a terminal apparatus via a packet-switched network, the input data including at least a target region identifier, an implementation period specification, and an upper expenditure limit value;
• acquiring reference data from a storage medium, the reference data including historical pattern data and trend information data;
• constructing a parameterized instruction sequence based on the input data and the reference data, the parameterized instruction sequence specifying a behavior plan generation task for a generative neural network model;
• providing the parameterized instruction sequence to the generative neural network model to cause the generative neural network model to generate behavior plan data including activity element data, movement resource data, facility resource data, and cost information data conforming to the implementation period specification and the upper expenditure limit value;
• and
• verifying the behavior plan data by determining consistency of aggregate cost values with the upper expenditure limit value and temporal consistency of scheduled elements with the implementation period specification.