1,721,072 research outputs found
Kernel functions for case-based planning
No full textCase-based planning can take advantage of former problem-solving experiences by storing in a plan library previously generated plans that can be reused to solve similar planning problems in the future. Although comparative worst-case complexity analyses of plan generation and reuse techniques reveal that it is not possible to achieve provable efficiency gain of reuse over generation, we show that the case-based planning approach can be an effective alternative to plan generation when similar reuse candidates can be chosen. In this paper we describe an innovative case-based planning system, called OAKplan, which can efficiently retrieve planning cases from plan libraries containing more than ten thousand cases, choose heuristically a suitable candidate and adapt it to provide a good quality solution plan which is similar to the one retrieved from the case library. Given a planning problem we encode it as a compact graph structure, that we call Planning Encoding Graph, which gives us a detailed description of the topology of the planning problem. By using this graph representation, we examine an approximate retrieval procedure based on kernel functions that effectively match planning instances, achieving extremely good performance in standard benchmark domains. The experimental results point out the effect of the case base size and the importance of accurate matching functions for global system performance. Overall, we show that OAKplan is competitive with state-of-the-art plan generation systems in terms of number of problems solved, CPU time, plan difference values and plan quality when cases similar to the current planning problem are available in the plan library. © 2010 Elsevier B.V. All rights reserved
Identifying and Exploiting Features for Effective Plan Retrieval in Case-Based Planning
Full text linkCase-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 extremely effective when
similar reuse candidates can be efficiently 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
of the instance that can be automatically derived from
the problem specification, domain and search space
analyses, and different problem encodings.
Since the use of existing planning features are not always
able to effectively distinguish between problems
within the same planning domain, we introduce a new
class of features.
An experimental analysis in this paper shows that our
features-based retrieval approach can significantly improve
the performance of a state-of-the-art case-based
planning system
Didactic and Pedagogical View of E-learning Activities Free University of Bozen-bolzano
No full textIn the knowledge and communication age, the contribution of technology, especially web 2.0, has transformed the concept of distance learning into that of e-learning and online learning. These are based on the use of CSCL (Computer Supported Collaborative Learning) and characterised by a pedagogical approach focussed on the learner, cooperative building of knowledge, and increasing the diversity of its learner base. Online learning represents a considerable opportunity for universities to promote larger and more democratic access to intellectual resources, reducing the social gap that is often related to on-site learning. However, using e-learning educational methods require careful consideration of different aspects and problems. This paper starts with a description of the most widely used open source e-learning platforms in Italian Universities. Furthermore, it proposes an analysis of the pedagogical and didactic potential of the tools offered by the Moodle platform and a reflection about the need to use guidelines to evaluate accessibility, also with reference to the Universal Instructional Design principles. In the final part, a study about the concrete use of specific Moodle activities in some courses at the University of Bolzano (empirical research and verification on field) is presented with the purpose of identifying methodological indications that could help to implement the educational and inclusive value of the online contexts
Planning as Propositional CSP: From Walksat to Local Search on Planning Graphs with Action Costs
No full textEfficient Plan Adaptation through Replanning Windows and Heuristic Goals
No full textFast plan adaptation is important in many AI applications. From a theoretical point of view, in the worst case adapting an existing plan to solve a new problem is no more efficient than a complete regeneration of the plan. However, in practice plan adaptation can be much more efficient than plan generation, especially when the adapted plan can be obtained by performing a limited amount of changes to the original plan. In this paper, we investigate a domain-independent method for plan adaptation that modifies the original plan by replanning within limited temporal windows containing portions of the plan that need to be revised. Each window is associated with a particular replanning subproblem that contains some “heuristic goals” facilitating the plan adaptation, and that can be solved using different planning methods. An experimental analysis shows that, in practice, adapting a given plan for solving a new problem using our techniques can be much more efficient than replanning from scratch
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