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Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition
- Journal of Artificial Intelligence Research
, 2000
"... This paper presents a new approach to hierarchical reinforcement learning based on decomposing the target Markov decision process (MDP) into a hierarchy of smaller MDPs and decomposing the value function of the target MDP into an additive combination of the value functions of the smaller MDPs. Th ..."
Abstract
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Cited by 443 (6 self)
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This paper presents a new approach to hierarchical reinforcement learning based on decomposing the target Markov decision process (MDP) into a hierarchy of smaller MDPs and decomposing the value function of the target MDP into an additive combination of the value functions of the smaller MDPs
Block Decomposition of Inheritance Hierarchies
- In Graph Theoretical Concept in Computer Science, WG'97, LNCS 1335
, 1997
"... . Inheritance hierarchies play a central role in object oriented languages as in knowledge representation systems. These hierarchies are acyclic directed graphs representing the underline structure of objects. This paper is devoted to the study of efficient algorithms to decompose recursively an inh ..."
Abstract
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Cited by 6 (1 self)
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an inheritance hierarchy into independent subgraphs which are inheritance hierarchies themselves. This process gives a tree called decomposition tree. The decomposition proposed here is based on the concept of block which is an extension of the concept of h-module proposed by R. Ducournau and M. Habib [7]. M
Faster and More Focused Control-Flow Analysis for Business Process Models through SESE Decomposition
, 2007
"... ..."
Feature hierarchies for object classification
, 2005
"... The paper describes a method for automatically extracting informative feature hierarchies for object classification, and shows the advantage of the features constructed hierarchically over previous methods. The extraction process proceeds in a top-down manner: informative top-level fragments are ext ..."
Abstract
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Cited by 59 (3 self)
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The paper describes a method for automatically extracting informative feature hierarchies for object classification, and shows the advantage of the features constructed hierarchically over previous methods. The extraction process proceeds in a top-down manner: informative top-level fragments
Hierarchical Control and Learning for Markov Decision Processes
, 1998
"... This dissertation investigates the use of hierarchy and problem decomposition as a means of solving large, stochastic, sequential decision problems. These problems are framed as Markov decision problems (MDPs). The new technical content of this dissertation begins with a discussion of the concept o ..."
Abstract
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Cited by 122 (2 self)
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This dissertation investigates the use of hierarchy and problem decomposition as a means of solving large, stochastic, sequential decision problems. These problems are framed as Markov decision problems (MDPs). The new technical content of this dissertation begins with a discussion of the concept
in declarative business process models
"... Investigating expressiveness and understandability of hierarchy ..."
E.: User Assistance for Business Process Model Decomposition
- In First IEEE International Conference on Research Challenges in Information Science
"... Abstract — Petri nets are a suitable language for modeling business processes with complex flow structures. Processes with a number of alternative, concurrent or sequential flow structures on the same process abstraction level may result in complex processes. Such complex and poorly unstructured pro ..."
Abstract
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Cited by 9 (2 self)
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Abstract — Petri nets are a suitable language for modeling business processes with complex flow structures. Processes with a number of alternative, concurrent or sequential flow structures on the same process abstraction level may result in complex processes. Such complex and poorly unstructured
Finding the Hierarchy of Dense Subgraphs using Nucleus Decompositions
"... Finding dense substructures in a graph is a fundamental graph mining operation, with applications in bioinformatics, social networks, and visualization to name a few. Yet most standard formulations of this problem (like clique, quasi-clique, k-densest subgraph) are NP-hard. Furthermore, the goal is ..."
Abstract
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Cited by 3 (1 self)
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providing any structural relations. We define the nucleus decomposition of a graph, which represents the graph as a forest of nuclei. Each nucleus is a subgraph where smaller cliques are present in many larger cliques. The forest of nuclei is a hierarchy by containment, where the edge density increases
Analytical Hierarchy Process in Requirements Analysis
, 1996
"... We describe a group of related approaches to quantitative evaluation and prioritization of system requirements and proposals. In formulating requirements for new systems, analysts face difficult tasks of selecting between alternative requirement decompositions, identifying questionable or low-priori ..."
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of the requirements formulation process. We show that the Analytical Hierarchy Process can be applied to provide such evaluation mechanisms and illustrate our approach with a detailed example.
Results 1 - 10
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724
