O-Plan: the open planning architecture
Ken Currie,Austin Tate +1 more
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TLDR
The search control heuristics employed within the O-Plan planner involve the use of condition typing, time and resource constraints and domain constraints to allow knowledge about an application domain to be used to prune the search for a solution.About:
This article is published in Artificial Intelligence.The article was published on 1991-11-01 and is currently open access. It has received 497 citations till now. The article focuses on the topics: Partial-order planning & Heuristics.read more
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Hierarchical reinforcement learning with the MAXQ value function decomposition
TL;DR: The paper presents an online model-free learning algorithm, MAXQ-Q, and proves that it converges with probability 1 to a kind of locally-optimal policy known as a recursively optimal policy, even in the presence of the five kinds of state abstraction.
Book
Artificial Intelligence: A New Synthesis
TL;DR: Intelligent agents are employed as the central characters in this new introductory text and Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI.
Journal ArticleDOI
The Enterprise Ontology
TL;DR: The Enterprise Ontology was developed within the Enterprise Project, a collaborative effort to provide a framework for enterprise modelling, and was built to serve as a basis for this framework which includes methods and a computer tool set for enterprise modeling.
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SHOP2: an HTN planning system
TL;DR: The SHOP2 planning system as discussed by the authors received one of the awards for distinguished performance in the 2002 International Planning Competition and described the features that enabled it to excel in the competition, especially those aspects of SHOP 2 that deal with temporal and metric planning domains.
Proceedings Article
Reinforcement Learning with Hierarchies of Machines
Ronald Parr,Stuart Russell +1 more
TL;DR: This work presents provably convergent algorithms for problem-solving and learning with hierarchical machines and demonstrates their effectiveness on a problem with several thousand states.
References
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Strips: A new approach to the application of theorem proving to problem solving
Richard Fikes,Nils J. Nilsson +1 more
TL;DR: In this paper, the authors describe a problem solver called STRIPS that attempts to find a sequence of operators in a space of world models to transform a given initial world model in which a given goal formula can be proven to be true.
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Introduction to sequencing and scheduling
TL;DR: In this article, the authors present an introduction to Sequencing and Scheduling in the context of the Operational Research Society (ORS) and the International Journal of Distributed Sensor Networks (ILS).
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A truth maintenance system
TL;DR: The need of problem solvers to choose between alternative systems of beliefs is stressed, and a mechanism by which a problem solver can employ rules guiding choices of what to believe, what to want, and what to do is outlined.
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An assumption-based TMS
TL;DR: A new view of problem solving motivated by a new kind of truth maintenance system based on manipulating assumption sets is presented, which is possible to work effectively and efficiently with inconsistent information, context switching is free, and most backtracking is avoided.
Book
A Structure for Plans and Behavior
TL;DR: Progress to date in the ability of a computer system to understand and reason about actions is described, and the structure of a plan of actions is as important for problem solving and execution monitoring as the nature of the actions themselves.