Most of the research in Automated Planning relies on the evaluation of different techniques over a set of benchmarks. The generation of planning tasks for these benchmarks is done using generators coded ad-hoc. Instead, we propose an approach for generating planning problems automatically given the domain definition and some declarative semanticsrelated information provided by the user. The app...

One of EU’s actions against climate change is to meet 20% of our energy needs from renewable resources. Given that the renewable resources are becoming more economical to extract electricity from, this will result in that more and more distributed generation (DG) will be connected to power distribution. The increasing share of DG in the electricity networks implies both increased costs and bene...

In this paper, we address the knowledge engineering problems for hypothesis generation motivated by applications that require timely exploration of hypotheses under unreliable observations. We looked at two applications: malware detection and intensive care delivery. In intensive care, the goal is to generate plausible hypotheses about the condition of the patient from clinical observations and...

It is a common practice in Automated Planning to evaluate algorithms on existing benchmark domains. The number of domain models is limited, since they are encoding simplified versions of real-world domains and the generation of a new planning domain is a complex task. The limited number of domain models does not allow to have a complete overview of the performances of automated planning engines...

We provide a production planning framework for variant rich customized products (such as automobiles, computers), by calculating entirely constructible configuration sets for future customer demands in a novel manner. Most of the established approaches analyse configurations out of historical order banks for estimating the appropriate set of future demands. In the current environment of rapidly...

As our understanding of natural language generation has increased, a number of tasks have been separated from realization and put together under the heading atext planning I . So far, however, no-one has enumerated the kinds of tasks a text planner should be able to do. This paper describes the principal lesson learned in combining a number of planning tasks in a planner-realiser: planning and ...

In this paper, system planning network is formulated with mixed-integer programming. Two meta-heuristic procedures are considered for this problem. The cost function of this problem consists of the capital investment cost in discrete form, the cost of transmission losses and the power generation costs. The DC load flow equations for the network are embedded in the constraints of the mathematica...

In this paper we discuss techniques for online generation of macro-actions as part of the planning process and demonstrate their use in a forwardchaining search planning framework. The macroactions learnt are specifically created at places in the search space where the heuristic is not informative. We present results to show that using macro-actions generated during planning can improve plannin...

We present a natural language generation approach which models, exploits, and manipulates the non-linguistic context in situated communication, using techniques from AI planning. We show how to generate instructions which deliberately guide the hearer to a location that is convenient for the generation of simple referring expressions, and how to generate referring expressions with context-depen...