International audienceKnowledge-based programs (KBPs) are high-level protocols describing the course of action an agent should perform as a function of its knowledge. The use of KBPs for expressing action policies in AI planning has been surprisingly overlooked. Given that to each KBP corresponds an equivalent plan and vice versa, KBPs are typically more succinct than standard plans, but imply more on-line computation time. Here we make this argument formal, and prove that there exists an exponential succinctness gap between knowledge-based programs and standard plans. Then we address the complexity of plan existence. Some results trivially follow from results already known from the literature on planning under incomplete knowledge, but man...
Knowledge-based programs, first introduced by Halpern and Fagin [HF89] and further developed by Fagi...
This paper introduces a framework for Planning while Learning where an agent is given a goal to achi...
Abstract: "This paper explores the issue of planning in two-person games using approximately learned...
International audienceKnowledge-based programs (KBPs) are high-level protocols describing the course...
International audienceKnowledge-based programs (KBPs) are high-level protocols describing the course...
Frontiers in Artificial Intelligence and Applications, vol. 242International audienceKnowledge-based...
International audienceKnowledge-based programs (KBPs) are high-level protocols describing the course...
Knowledge-based programs (KBPs) are high-level protocols describing the course of action an agent sh...
Abstract. Knowledge-based programs (KBPs) are high-level pro-tocols describing the course of action ...
International audienceWe suggest to express policies for contingent planning by knowledge-based prog...
AbstractIn this paper we discuss techniques for representing and organizing knowledge that enable a ...
Planning is a very important AI problem, and it is also a very time-consuming AI problem. To get an ...
For an agent to be able to rely on a plan, he must know both that he is physically capable of carryi...
International audienceWe introduce Probabilistic Knowledge-Based Programs (PKBPs), a new, compact re...
AbstractKnowledge-based proof planning is a new paradigm in automated theorem proving (ATP) which sw...
Knowledge-based programs, first introduced by Halpern and Fagin [HF89] and further developed by Fagi...
This paper introduces a framework for Planning while Learning where an agent is given a goal to achi...
Abstract: "This paper explores the issue of planning in two-person games using approximately learned...
International audienceKnowledge-based programs (KBPs) are high-level protocols describing the course...
International audienceKnowledge-based programs (KBPs) are high-level protocols describing the course...
Frontiers in Artificial Intelligence and Applications, vol. 242International audienceKnowledge-based...
International audienceKnowledge-based programs (KBPs) are high-level protocols describing the course...
Knowledge-based programs (KBPs) are high-level protocols describing the course of action an agent sh...
Abstract. Knowledge-based programs (KBPs) are high-level pro-tocols describing the course of action ...
International audienceWe suggest to express policies for contingent planning by knowledge-based prog...
AbstractIn this paper we discuss techniques for representing and organizing knowledge that enable a ...
Planning is a very important AI problem, and it is also a very time-consuming AI problem. To get an ...
For an agent to be able to rely on a plan, he must know both that he is physically capable of carryi...
International audienceWe introduce Probabilistic Knowledge-Based Programs (PKBPs), a new, compact re...
AbstractKnowledge-based proof planning is a new paradigm in automated theorem proving (ATP) which sw...
Knowledge-based programs, first introduced by Halpern and Fagin [HF89] and further developed by Fagi...
This paper introduces a framework for Planning while Learning where an agent is given a goal to achi...
Abstract: "This paper explores the issue of planning in two-person games using approximately learned...