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1

Identifying and Exploiting Features for Effective Plan Retrieval in Case-Based Planning

Vallati M., Serina I., Saetti A., Gerevini A. E.

Fundamenta Informaticae

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2016

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Vol. 149, nr 1/2

209--240

EN

Case-based planning can fruitfully exploit knowledge gained by solving a large number of problems, storing the corresponding solutions in a plan library and reusing them for solving similar planning problems in the future. Case-based planning is very effective when similar reuse candidates can be efficiently and effectively chosen. In this paper, we study an innovative technique based on planning problem features for efficiently retrieving solved planning problems (and relative plans) from large plan libraries. A problem feature is a characteristic –usually provided under the form of a number– of the instance that can be automatically derived from the problem specification, domain and search space analyses, or different problem encodings. Given a planning problem to solve, its features are extracted and compared to those of problems stored in the case base, in order to identify most similar problems. Since the use of existing planning features is not always able to effectively distinguish between problems within the same planning domain, we introduce a large number of new features. An experimental analysis in this paper investigates the best set of features to be exploited for retrieving plans in case-based planning, and shows that our feature-based retrieval approach can significantly improve the performance of a state-of-the-art case-based planning system.

2

A Domain Knowledge as a Tool For Improving Classifiers

Bazan J.G., Buregwa-Czuma S., Jankowski A. W.

Fundamenta Informaticae

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2013

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Vol. 127, nr 1-4

495--511

EN

This paper investigates the approaches to an improvement of classifiers quality through the application of a domain knowledge. The expertise may be utilizable on several levels of decision algorithms such as: feature extraction, feature selection, a definition of temporal patterns used in an approximation of the concepts, especially of the complex spatio-temporal ones, an assignment of an object to the concept and a measurement of the objects similarity. The domain knowledge incorporation results then in the reduction of the size of searched spaces. The work constitutes an overview of classifier building methods efficiently utilizing the expertise, worked out latterly by Professor Andrzej Skowron research group. The methods using domain knowledge intended to enhance the quality of classic classifiers, to identify the behavioral patterns and for automatic planning are discussed. Finally it answers a question whether the methods satisfy the hopes vested in them and indicates the directions for future development.

3

An Empirical Analysis of Some Heuristic Features for Planning through Local Search and Action Graphs

Gerevini A., Saetti A., Serina I.

Fundamenta Informaticae

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2011

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Vol. 107, nr 2/3

167-197

EN

Planning through local search and action graphs is a powerful approach to fully-automated planning which is implemented in the well-known LPG planner. The approach is based on a stochastic local search procedure exploring a space of partial plans and several heuristic features with different possible options. In this paper, we experimentally analyze the most important of them, with the goal of understanding and evaluating their impact on the performance of LPG, and of identifying default settings that work well on a large class of problems. In particular, we analyze several heuristic techniques for (a) evaluating the search neighborhood, (b) defining/restricting the search neighborhood, (c) selecting the next plan flaw to handle, (d) setting the "noise" parameter randomizing the search, and (e) computing reachability information that can be exploited by the heuristic functions used to evaluate the neighborhood elements. Some of these techniques were introduced in previous work on LPG, while others are new. Additional experimental results indicate that the current version of LPG using the identified best heuristic techniques as the default settings is competitive with the winner of the last (2008) International Planning Competition.

4

Zagadnienia zautomatyzowanego planowania ruchów robotów przemysłowych w elastycznych systemach montażowych

Kyrylovich V., Bogdanowski M.

Technologia i Automatyzacja Montażu

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2009

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nr 1

18-22

EN

The progress of the methods of automated kinematical forming of industrial robots program trajectory of gripping devise for robotic assembly technology synthesis concerned with dynamic optimization of program motion has been presented. The structure and content of solving tasks have been described.

5

Case-based Planning of Treatment of Infants with Respiratory Failure

Góra G., Bazan J.G., Kruczek P., Bazan-Socha S., Skowron A., Pietrzyk J.J.

Fundamenta Informaticae

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2008

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Vol. 85, nr 1-4

155-172

EN

We discuss medical treatment planning in the context of case-based planning, where plans (of treatment) are treated as complex decisions. A plan for a particular case is constructed from known plans for similar training examples. In order to evaluate and improve the prediction quality of complex decisions, we use a method for approximation of similarity measure between plans. The method makes it possible to transform the acquired domain knowledge about similarities of plans, expressed by medical experts in natural language, to a low level language understandable by the system. To accomplish this task, we developed a method for approximation of the ontology of concepts expressed by medical experts. We present two applications of the ontology approximation, namely, for approximation of similarity between patient histories and for approximation of compatibility of patient histories with planned therapies. Next, we use these concept approximations to define two measures on which are based two methods for (plan) therapy prediction. The article includes results of experiments with these methods performed on medical data obtained from Neonatal Intensive Care Unit, First Department of Pediatrics, Polish-American Institute of Pediatrics, Collegium Medicum, Jagiellonian University, Kraków, Poland. The experiments are pertained to the identification of infants' death risk caused by respiratory failure.