Periodic Reporting for period 2 - AIPlan4EU (Bringing AI Planning to the European AI On-Demand Platform)
Reporting period: 2022-07-01 to 2023-12-31
Automated Planning and Scheduling is a central research area in AI that has been studied since the inception of the field and where European research has been making strong contributions over decades. Planning is a decision-making technology that consists in reasoning on a predictive model of a system being controlled and deciding how and when to act in order to achieve a desired objective. It is a relevant technology for many application areas that need quick, automated and optimal decisions, like agile manufacturing, agrifood or logistics.
The AIPlan4EU project brought AI planning as a first-class citizen in the European AI On-Demand (AIoD) Platform by developing a uniform, user-centered framework to access the existing planning technology and by devising concrete guidelines for innovators and practitioners on how to use this technology. We considered use-cases from diverse application areas that inspired the design and the development of the framework, and included several available planning systems as engines that can be selected to solve practical problems. We developed a general and planner-agnostic API that is available as a resource to be integrated into the users' systems and is also available through the AI Builder component of the AIoD platform. The framework has been validated on use-cases both from within the consortium and recruited by means of cascade funding; moreover, standard interfaces between the framework and common industrial technologies have been developed.
The main project output is the “Unified Planning Framework” (UPF, https://github.com/aiplan4eu/unified-planning)(opens in new window): a single-access-point service for using and experimenting with planning technology. Planning engines can be used through the UPF by means of a dynamic plugin system. This means that a user can pose planning queries in an engine-independent way and the UPF is capable of discovering, among the available engines, the ones capable of answering the query and can adapt the query to the specificities of the selected engine by means of the engine-dependent plugin.
We also realized solutions prototypes for the use-cases elicited within the project. Each use-case focused on a specific technology to perform its business logic and there is the need of interfacing the specificities of such technologies to the UPF API/language. Hence, we designed and developed Technology Specific Bridges (TSBs) as reusable software components that are used to realize the solution of the various use-cases.
Finally, an overarching objective of the project was to bring this grand view to the AIoD platform. We provided our solutions as downloadable AI-assets and we allow user experimentation with our planning technology and use-cases directly on the platform by means of the AI Builder, which offers a reusable unified planning server component and several interactive planning demonstrations.
The AIPlan4EU project brought AI planning as a first-class citizen in the European AI On-Demand (AIoD) Platform by developing a uniform, user-centered framework to access the existing planning technology and by devising concrete guidelines for innovators and practitioners on how to use this technology. We considered use-cases from diverse application areas that inspired the design and the development of the framework, and included several available planning systems as engines that can be selected to solve practical problems. We developed a general and planner-agnostic API that is available as a resource to be integrated into the users' systems and is also available through the AI Builder component of the AIoD platform. The framework has been validated on use-cases both from within the consortium and recruited by means of cascade funding; moreover, standard interfaces between the framework and common industrial technologies have been developed.
The main project output is the “Unified Planning Framework” (UPF, https://github.com/aiplan4eu/unified-planning)(opens in new window): a single-access-point service for using and experimenting with planning technology. Planning engines can be used through the UPF by means of a dynamic plugin system. This means that a user can pose planning queries in an engine-independent way and the UPF is capable of discovering, among the available engines, the ones capable of answering the query and can adapt the query to the specificities of the selected engine by means of the engine-dependent plugin.
We also realized solutions prototypes for the use-cases elicited within the project. Each use-case focused on a specific technology to perform its business logic and there is the need of interfacing the specificities of such technologies to the UPF API/language. Hence, we designed and developed Technology Specific Bridges (TSBs) as reusable software components that are used to realize the solution of the various use-cases.
Finally, an overarching objective of the project was to bring this grand view to the AIoD platform. We provided our solutions as downloadable AI-assets and we allow user experimentation with our planning technology and use-cases directly on the platform by means of the AI Builder, which offers a reusable unified planning server component and several interactive planning demonstrations.
WP1:
Administrative activities, management and documentation
WP2:
Requirements definition in order to identify and describe the planning problem emerging in each use-case and clarify its objective. Support for the evaluation of the open-calls for use-cases.
WP3:
Design and develop of the UPF prototype, making it ready to be integrated with planning engines and TSBs. The UPF is publicly developed and available as an open-source python library.
WP4:
Integration of several planning engines as plug-ins to the UPF. Definition of the test cases repository. Analysis and identification of the targeted planning engines available in the literature.
WP5:
Definition of the general integration principles and a general architecture for the TSBs. Design and implementation of the TSBs for the various demonstrators for the use-cases emerging from project partners.
WP6:
Definition of the general evaluation methodology and evaluation of the requirements for the UPF, the TSBs and the planning engines.
WP7:
Deep collaboration and coordination with the other ICT49 projects, publication of resources in the European AI On-Demnad Platform and preparation of several demonstrators within the AI4EU Experiments Platform.
WP8:
Communication platforms. Dissemination of open-calls. Participation to the ICAPS demo session. Write articles related to planning. Promote AIPLAN4EU to international conferences.
WP9:
Helped project partners and external stakeholders in the definition of an exploitation plan for the innovative solutions based on AIPlan4EU.
WP10:
Issued, evlauated them and organized the open calls of the project.
Administrative activities, management and documentation
WP2:
Requirements definition in order to identify and describe the planning problem emerging in each use-case and clarify its objective. Support for the evaluation of the open-calls for use-cases.
WP3:
Design and develop of the UPF prototype, making it ready to be integrated with planning engines and TSBs. The UPF is publicly developed and available as an open-source python library.
WP4:
Integration of several planning engines as plug-ins to the UPF. Definition of the test cases repository. Analysis and identification of the targeted planning engines available in the literature.
WP5:
Definition of the general integration principles and a general architecture for the TSBs. Design and implementation of the TSBs for the various demonstrators for the use-cases emerging from project partners.
WP6:
Definition of the general evaluation methodology and evaluation of the requirements for the UPF, the TSBs and the planning engines.
WP7:
Deep collaboration and coordination with the other ICT49 projects, publication of resources in the European AI On-Demnad Platform and preparation of several demonstrators within the AI4EU Experiments Platform.
WP8:
Communication platforms. Dissemination of open-calls. Participation to the ICAPS demo session. Write articles related to planning. Promote AIPLAN4EU to international conferences.
WP9:
Helped project partners and external stakeholders in the definition of an exploitation plan for the innovative solutions based on AIPlan4EU.
WP10:
Issued, evlauated them and organized the open calls of the project.
The project developed a novel platform, called Unified Planning Framework (UPF) providing an abstraction layer for planning services that aims to facilitate and streamline the use of planning technology in practice. The development of the UPF follows an open-source, agile methodology with a public GitHub repository (https://github.com/aiplan4eu/unified-planning(opens in new window)) where issues and user-stories are discussed, and the developers discuss publicly about design choices and APIs. For the design of the UPF we followed user-centered design principles, where the various features are backed by user-stories detailing the intended use and serve as informal documentation of the requirement. The UPF is incarnated as an open-source Python3 library, which offers a unified API for the specification and manipulation of planning problems and integrates a number of planning engines (integrated by the project and available at https://github.com/aiplan4eu(opens in new window)) which offer planning technology services. The library has been developed following the best practices for open-source python development and offers a comprehensive API for classical, numeric, temporal, HTN, task-and-motion, contingent and multi-agent planning problems. Moreover we support simple scheduling problems. The UPF is well documented at code level and we created a number of Python Notebooks to showcase its use.
In addition to the UPF itself, we constructed a software ecosystem of reusable components to use planning technologies in different application sectors (TSBs). Examples include the interfacing with the Robot Operating System (ROS) and the Embedded Systems Bridge.
We worked for the integration of the UPF and other planning materials in the European AI On-Demand Platform (see https://www.ai4europe.eu/ai-community/projects/aiplan4eu(opens in new window)) in two main directions, namely the publication of planning related resources in the AI on demand platform and the realization of several AI4EU Experiments pipelines showing how to use planning technology via the UPF in the AI4EU Experiments Marketplace and AI4EU Playground. These pipleines are accompanied by support open-source software to simplify the realization of user-defined pipelines.
In addition to the UPF itself, we constructed a software ecosystem of reusable components to use planning technologies in different application sectors (TSBs). Examples include the interfacing with the Robot Operating System (ROS) and the Embedded Systems Bridge.
We worked for the integration of the UPF and other planning materials in the European AI On-Demand Platform (see https://www.ai4europe.eu/ai-community/projects/aiplan4eu(opens in new window)) in two main directions, namely the publication of planning related resources in the AI on demand platform and the realization of several AI4EU Experiments pipelines showing how to use planning technology via the UPF in the AI4EU Experiments Marketplace and AI4EU Playground. These pipleines are accompanied by support open-source software to simplify the realization of user-defined pipelines.