Augmenting CILEMP to Enable Fleet Autonomy with Generative AI (CILEMP-FLAG)
A Generative AI augmentation to the KnexPlan planning suite that extracts complex planning models and situational data from structured text and generates Navy-compliant operations orders (OPORDs), reports, and C2 messages in natural language.
PROBLEM
Existing automated planning systems rely on structured data to encode environment information, possible actions, and other relevant planning information.
They cannot effectively ingest operational knowledge or extract critical plan models and situation data from unstructured sources like text reports or human subject matter expert (SME) inputs. This leads to three key limitations: development requires slow, expensive model engineering using specialized languages; operators require extensive technical skills to work with automated planning systems; and semantic interoperability between diverse autonomous platforms is challenging, hindering the scale of fleet autonomy.
Knexus Solutions
SOLUTION
Knexus developed CILEMP-FLAG (Fleet Autonomy with Generative AI) to solve these limitations by incorporating advanced Generative AI capabilities into the existing KnexPlan foundation. This enhanced capability comprises mission identification, planning, and C2 for collaborative, heterogeneous platforms across entire kill chains.
CILEMP-FLAG uses a novel Generative AI architecture to automate the conversion between human interpretable descriptions and structed representations that can be used by automated planning systems:
Planning Knowledge Extractions
Ability to convert between natural language and structured planning representations even when those representations are complex and have limited examples/documentation. Provides the ability for non-technical users to modify planning knowledge, decreasing the skill requirements and time required.
Support for Complex Representations
Use of an agentic-inspired approach to subdivide the extraction process into simpler subproblems, allowing CILEMP-FLAG to generate planning knowledge even when more complex representations are used (e.g., that include timing, scheduling, and continuous numeric values).
Plan Queries
Provides the ability for a user to query system outputs (e.g., plans, simulation logs) and get clear, natural language responses on topics of interest, performance, and other relevant topics.
Customer Outcome
CUSTOMER OUTCOME
CILEMP-FLAG streamlines and scales autonomous planning systems by removing the need for specialized model engineering languages, allowing developers to generate models from plain text.
This allows advanced planning technology to be used even when access to technical experts is limited, allowing for rapid changes to planning knowledge, assumptions, and capabilities. In addition to the increased warfighter readiness and strategic planning capabilities, CILEMP-FLAG also provides significant manpower, time, and cost savings.
Augmenting CILEMP to Enable Fleet Autonomy with Generative AI (CILEMP-FLAG)
A Generative AI augmentation to the KnexPlan planning suite that extracts complex planning models and situational data from structured text and generates Navy-compliant operations orders (OPORDs), reports, and C2 messages in natural language.
Augmenting CILEMP to Enable Fleet Autonomy with Generative AI (CILEMP-FLAG)
PROBLEM
Existing automated planning systems rely on structured data to encode environment information, possible actions, and other relevant planning information.
They cannot effectively ingest operational knowledge or extract critical plan models and situation data from unstructured sources like text reports or human subject matter expert (SME) inputs. This leads to three key limitations: development requires slow, expensive model engineering using specialized languages; operators require extensive technical skills to work with automated planning systems; and semantic interoperability between diverse autonomous platforms is challenging, hindering the scale of fleet autonomy.
Knexus
Solution
Knexus developed CILEMP-FLAG (Fleet Autonomy with Generative AI) to solve these limitations by incorporating advanced Generative AI capabilities into the existing KnexPlan foundation. This enhanced capability comprises mission identification, planning, and C2 for collaborative, heterogeneous platforms across entire kill chains.
CILEMP-FLAG uses a novel Generative AI architecture to automate the conversion between human interpretable descriptions and structed representations that can be used by automated planning systems:
Planning Knowledge Extractions: Ability to convert between natural language and structured planning representations even when those representations are complex and have limited examples/documentation. Provides the ability for non-technical users to modify planning knowledge, decreasing the skill requirements and time required.
Support for Complex Representations: Use of an agentic-inspired approach to subdivide the extraction process into simpler subproblems, allowing CILEMP-FLAG to generate planning knowledge even when more complex representations are used (e.g., that include timing, scheduling, and continuous numeric values).
Plan Queries: Provides the ability for a user to query system outputs (e.g., plans, simulation logs) and get clear, natural language responses on topics of interest, performance, and other relevant topics.
Customer Outcome
Customer Outcome
Augmenting CILEMP to Enable Fleet Autonomy with Generative AI (CILEMP-FLAG)
CILEMP-FLAG uses a novel Generative AI architecture to automate the conversion between human interpretable descriptions and structed representations that can be used by automated planning systems:
This allows advanced planning technology to be used even when access to technical experts is limited, allowing for rapid changes to planning knowledge, assumptions, and capabilities. In addition to the increased warfighter readiness and strategic planning capabilities, CILEMP-FLAG also provides significant manpower, time, and cost savings.
