Presented at KEPS 2022 Workshop on Knowledge Engineering for Planning and Scheduling at the 32nd International Conference on Automated Planning and Scheduling (ICAPS). Abstract As individual sub-fields of AI become more developed, it becomes increasingly important to study their integration into complex systems. In this paper, we look at three examples of how automated planning can be integrated with learning and reasoning. We then provide a first look at the AI Domain Definition Language (AIDDL) as an attempt to provide a common ground for modeling problems, data, solutions, and their integration across all branches of AI in a common language
An autonomous agent architecture, in which Machine Learning and Planning are integrated, is presente...
This paper describes a system that uses AI planning and representation techniques as the core of a d...
Automated planning plays an important role in many fields of human interest, where complex and chang...
Planning is the branch of Artificial Intelligence (AI) that seeks to automate reasoning about plans,...
The Planning Domain Definition Language (PDDL) is a formal specification language for symbolic plann...
Automated planning is a central area of artificial intelli-gence, involving the design of languages ...
AbstractIn this paper we discuss techniques for representing and organizing knowledge that enable a ...
We propose revisions to the research agenda in Automated Planning. The proposal is based on a review...
In this paper we present the architecture and the abilities of the ModPlan Workbench; an interacive ...
Knowledge engineering in AI planning is the process that deals with the acquisition, validation and ...
The Planning Domain Definition Language (PDDL) successfully encodes classical planning tasks by easi...
The AI Planning field has pursued the goal of applying all developments already achieved in order to...
We consider techniques for learning to plan in deterministic and stochastic Artificial Intelligence ...
Despite the progress in automated planning and scheduling systems, these systems still need to be fe...
Abstract: Realistic planning systems must allow users and computer systems to co-operate and work to...
An autonomous agent architecture, in which Machine Learning and Planning are integrated, is presente...
This paper describes a system that uses AI planning and representation techniques as the core of a d...
Automated planning plays an important role in many fields of human interest, where complex and chang...
Planning is the branch of Artificial Intelligence (AI) that seeks to automate reasoning about plans,...
The Planning Domain Definition Language (PDDL) is a formal specification language for symbolic plann...
Automated planning is a central area of artificial intelli-gence, involving the design of languages ...
AbstractIn this paper we discuss techniques for representing and organizing knowledge that enable a ...
We propose revisions to the research agenda in Automated Planning. The proposal is based on a review...
In this paper we present the architecture and the abilities of the ModPlan Workbench; an interacive ...
Knowledge engineering in AI planning is the process that deals with the acquisition, validation and ...
The Planning Domain Definition Language (PDDL) successfully encodes classical planning tasks by easi...
The AI Planning field has pursued the goal of applying all developments already achieved in order to...
We consider techniques for learning to plan in deterministic and stochastic Artificial Intelligence ...
Despite the progress in automated planning and scheduling systems, these systems still need to be fe...
Abstract: Realistic planning systems must allow users and computer systems to co-operate and work to...
An autonomous agent architecture, in which Machine Learning and Planning are integrated, is presente...
This paper describes a system that uses AI planning and representation techniques as the core of a d...
Automated planning plays an important role in many fields of human interest, where complex and chang...