Nowadays, solving many important real-world problems require the use of Artificial Intelligence planning, scheduling and constraint satisfaction. For instance, synchronizing the on-board activities of a space mission while performing navigation tasks, satisfying the external constraints, coordinating the movement of personnel and supplies to support disaster relief efforts, and managing the flow of materials through an automated manufacturing facility are practical applications where planning and scheduling are highly coupled, and resources must be allocated to optimize overall performance objectives (e.g., maximizing scientific return of space missions, initiating relief efforts as soon as possible or maximizing product throughput). Consequently, solutions to these problems must integrate resource allocation, constraint satisfaction and plan synthesis capabilities among others. In short, we need to manage complex problems where planning, scheduling and constraint satisfaction must be interrelated, which entail a great potential for search techniques, algorithms and heuristics.

The main aim of this workshop is to join researchers of the field of Artificial Intelligence working on planning, scheduling, constraint satisfaction problems (CSPs), and related areas. In fact, we expect works based on different approaches that combine models of constraints and planning, scheduling and planning, planning and scheduling, heuristic applications of search, etc.

Accepted Papers

NEW: A new CFP is open to submit Works In Progress.

NOTE: Selected papers will be published in the journal "Inteligencia Artificial. Revista Iberoamericana de IA"