Add to ORKGWe present some preliminary work on modeling AI planning as a Mixed Integer Programming (MIP) problem. We discuss the main advantages and disadvantages of the approach and compare it to traditional planning frameworks. We investigate a number of MIP models of specific problems, each of them exploiting different strengths of the MIP formulation, and present our computational experience with these models
Compilation techniques in planning reformulate a problem into an alternative encoding for which effi...
This paper discusses mixed-integer programming (MIP) approaches to planning and scheduling in electr...
AbstractWe provide formulation techniques for obtaining sharp (i.e., convex hull) mixed integer prog...
We present some preliminary work on modeling AI planning as a Mixed Integer Programming (MIP) proble...
International audienceThis paper presents a review of past and present results and approaches in the...
This textbook provides a comprehensive modeling, reformulation and optimization approach for solving...
This paper describes ILP-PLAN, a framework for solving AI planning problems represented as integer l...
Planning has made significant progress since its inception in the 1970s, in terms both of the effici...
The conventional wisdom in the planning community is that planners based on integer programming (IP)...
Our goal here is to explore the interplay of constraints and planning, highlighting the differences ...
Recent research has shown the promise of using propositional reasoning and search to solve AI planni...
Technical systems evolve from simple dedicated task solvers to cooperative and competent assistants,...
Abstract: Realistic planning systems must allow users and computer systems to co-operate and work to...
Colloque avec actes et comité de lecture. internationale.International audiencePart of the recent wo...
An AI planning problem is one in which an agent capable of perceiving certain states and of performi...
Compilation techniques in planning reformulate a problem into an alternative encoding for which effi...
This paper discusses mixed-integer programming (MIP) approaches to planning and scheduling in electr...
AbstractWe provide formulation techniques for obtaining sharp (i.e., convex hull) mixed integer prog...
We present some preliminary work on modeling AI planning as a Mixed Integer Programming (MIP) proble...
International audienceThis paper presents a review of past and present results and approaches in the...
This textbook provides a comprehensive modeling, reformulation and optimization approach for solving...
This paper describes ILP-PLAN, a framework for solving AI planning problems represented as integer l...
Planning has made significant progress since its inception in the 1970s, in terms both of the effici...
The conventional wisdom in the planning community is that planners based on integer programming (IP)...
Our goal here is to explore the interplay of constraints and planning, highlighting the differences ...
Recent research has shown the promise of using propositional reasoning and search to solve AI planni...
Technical systems evolve from simple dedicated task solvers to cooperative and competent assistants,...
Abstract: Realistic planning systems must allow users and computer systems to co-operate and work to...
Colloque avec actes et comité de lecture. internationale.International audiencePart of the recent wo...
An AI planning problem is one in which an agent capable of perceiving certain states and of performi...
Compilation techniques in planning reformulate a problem into an alternative encoding for which effi...
This paper discusses mixed-integer programming (MIP) approaches to planning and scheduling in electr...
AbstractWe provide formulation techniques for obtaining sharp (i.e., convex hull) mixed integer prog...