Open AccessProceedings Article
Success in spades: using AI planning techniques to win the world championship of computer bridge
Stephen J. J. Smith,Dana S. Nau,Thomas A. Throop +2 more
- pp 1079-1086
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TLDR
The latest world-championship competition for computer bridge programs was the Baron Barclay World Bridge Computer Challenge, hosted in July 1997 by the American Contract Bridge League, and the winner was a new version of Great Game Products' Bridge Baron program, which uses Hierarchical Task-Network planning techniques.Abstract:
The latest world-championship competition for computer bridge programs was the Baron Barclay World Bridge Computer Challenge, hosted in July 1997 by the American Contract Bridge League. As reported in The New York Times and The Washington Post, the competition's winner was a new version of Great Game Products' Bridge Baron program. This version, Bridge Baron 8, has since gone on the market; and during the last three months of 1997 it was purchased by more than 1000 customers.The Bridge Baron's success also represents a significant success for research on AI planning systems, because Bridge Baron 8 uses Hierarchical Task-Network (HTN) planning techniques to plan its declarer play. This paper gives an overview of those techniques and how they are used.read more
Citations
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Planning in Answer Set Programming using Ordered Task Decomposition.
TL;DR: In this paper, a formalism for solving Hierarchical Task Network (HTN) planning using Answer Set Programming (ASP) is introduced, and a translation method from SHOP's representation of the planning problem into logic programs with negation is presented.
Journal ArticleDOI
Learning Without Human Expertise: A Case Study of the Double Dummy Bridge Problem
TL;DR: A detailed comparison between various data representations of the DDBP solved by neural networks is provided, finding that both the numerical figures and weight patterns are stable and repeatable in a sample of neural architectures.
Journal ArticleDOI
A work point count system coupled with back-propagation for solving double dummy bridge problem
R. Amalraj,M. Dharmalingam +1 more
TL;DR: The Cascade Correlation Neural Network architecture with supervised learning implemented to train data and hence to test it is coupled along with Work point count system, which is the key idea behind the Double Dummy Bridge Problem.
Proceedings ArticleDOI
Automated learning of hierarchical task networks for controlling minecraft agents
TL;DR: An agent that learns Hierarchical Task Network knowledge from observing a player performing actions in Minecraft and learning the tasks that the player pursues and how to achieve these tasks is presented.
Dissertation
Plan projection, execution, and learning for mobile robot control.
TL;DR: This thesis proposes to base plan execution on plan projection and learning and presents a general framework for the self-supervised improvement of plan execution and contributes to the field of plan-based mobile robot control which investigates the interrelation between planning, reasoning, and learning techniques.
References
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Journal ArticleDOI
Planning in a hierarchy of abstraction spaces
TL;DR: Examples of the ABSTRIPS system's performance are presented that demonstrate the significant increases in problem-solving power that this approach provides, and some further implications of the hierarchical planning approach are explored.
Proceedings Article
HTN planning: complexity and expressivity
TL;DR: How the complexity of HTN planning varies with various conditions on the task networks is described.
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Generating project networks
TL;DR: The planner (NONLIN) and the Task Formalism (TF) used to hierarchically specify a domain are described, which can aid in the generation of project networks.
Proceedings Article
Planning in a hierarchy of abstraction spaces
TL;DR: Examples of the ABSTRIPS system's performance are presented that demonstrate the significant increases in problem-solving power that this approach provides, and some further implications of the hierarchical planning approach are explored.
Proceedings Article
UMCP: a sound and complete procedure for hierarchical task-network planning
TL;DR: This paper presents a formal syntax and semantics for HTn planning and is able to define an algorithm for HTN planning and prove it sound and complete.