Backwards State-space Reduction for Planning in Dynamic Knowledge Bases

In this paper we address the problem of planning in rich domains, where knowledge representation is a key aspect for managing the complexity and size of the planning domain. We follow the approach of Description Logic (DL) based Dynamic Knowledge Bases, where a state of the world is represented concisely by a (possibly changing) ABox and a (fixed) TBox containing the axioms, and actions that allow to change the content of the ABox. The plan goal is given in terms of satisfaction of a DL query. In this paper we start from a traditional forward planning algorithm and we propose a much more efficient variant by combining backward and forward search. In particular, we propose a Backward State-space Reduction technique that consists in two phases: first, an Abstract Planning Graph P is created by using the Abstract Backward Planning Algorithm (ABP), then the abstract planning graph P is instantiated into a corresponding planning graph P by using the Forward Plan Instantiation Algorithm (FPI). The advantage is that in the preliminary ABP phase we produce a symbolic plan that is a pattern to direct the search of the concrete plan. This can be seen as a kind of informed search where the preliminary backward phase is useful to discover properties of the state-space that can be used to direct the subsequent forward phase. We evaluate the effectiveness of our ABP+FPI algorithm in the reduction of the explored planning domain by comparing it to a standard forward planning algorithm and applying both of them to a concrete business case study.Comment: In Proceedings GRAPHITE 2014, arXiv:1407.767

Synthesizing and executing plans in Knowledge and Action Bases

We study plan synthesis for a variant of Knowledge and Action Bases (KABs). KABs have been recently introduced as a rich, dynamic framework where states are full-fledged description logic (DL) knowledge bases (KBs) whose extensional part is manipulated by actions that can introduce new objects from an infinite domain. We show that, in general, plan existence over KABs is undecidable even under severe restrictions. We then focus on the class of state-bounded KABs, for which plan existence is decidable, and we provide sound and complete plan synthesis algorithms, through a novel combination of techniques based on standard planning, DL query answering, and finite-state abstractions. All results hold for any DL with decidable query answering. We finally show that for lightweight DLs, plan synthesis can be compiled into standard ADL planning. © 2016, CEUR-WS. All rights reserved

Plan Synthesis for Knowledge and Action Bases

We study plan synthesis for a variant of Knowledge and Action Bases (KABs), a rich, dynamic framework, where states are description logic (DL) knowledge bases (KBs) whose extensional part is manipulated by actions that possibly introduce new objects from an infinite domain. We show that plan existence over KABs is undecidable even under severe restrictions. We then focus on state-bounded KABs, a class for which plan existence is decidable, and provide sound and complete plan synthesis algorithms, which combine techniques based on standard planning, DL query answering, and finite-state abstraction. All results hold for any DL with decidable query answering. We finally show that for lightweight DLs, plan synthesis can be compiled into standard ADL planning

The repurchase of own shares by public companies and Aktiengesellschaften

For the German observer the idea of a Company repurchasing its own shares seems to resemble the picture of a snake eating its own tail. It appears to be highly unnatura1 and one wonders how the tail tan possibly be eatable for the snake. Not in the United States. Although repurchases have once been subject to the most stubbornly fought conflict in US Company law only some modest disclosure requirements and safeguards against overt market manipulation exist today. Large repurchases are an almost everyday event and there is an increasing tendency. The aggregate value of shares repurchased by NYSE listed companies has increased from $1 .l billion in 1975 to$ 6.3 billion in 1982 to $37.1 billion in 1985*. Few examples may illustrate this practice further: Within three years Ford Motor Corp. repurchased 30 million shares for$ 1.2 billion. In 1985 Phillips Petroleum Corp. was faced with two hostile bids and took several defensive Steps, one of which was to tender for 20 million of its own shares at a total tost of $1 billion. And by the end of 1988 Exxon Corp. retired 28 percent of its shares that had once been outstanding at an aggregate tost of$ 14.5 billion. The Situation in Germany is completely different. As it will be shown under German law repurchases are severely restricted and do appreciable amount at all. not take place at an In contrast to German law the United Kingdom does not prohibit repurchases but requires companies to comply with such complex rules that US companies would regard simply as limiting their economic freedom. Therefore UK companies very seldom repurchase their own shares, too. This Paper deals with repurchases by quoted companies, in particular the UK public Company and the more or less German equivalent, the Aktiengesellschaft (AG). It seeks to ascertain the reasons why companies might want to engage in those activities. Moreover, it tries to analyse the Problems which may arise from repurchases and the safeguards which the UK and German legal Systems provide for these Problems.This Paper deals with repurchases by quoted companies, in particular the UK public Company and the more or less German equivalent, the Aktiengesellschaft (AG). It seeks to ascertain the reasons why companies might want to engage in those activities. Moreover, it tries to analyse the Problems which may arise from repurchases and the safeguards which the UK and German legal Systems provide for these Problems

Models and Algorithms for Production Planning and Scheduling in Foundries – Current State and Development Perspectives

Mathematical programming, constraint programming and computational intelligence techniques, presented in the literature in the field of operations research and production management, are generally inadequate for planning real-life production process. These methods are in fact dedicated to solving the standard problems such as shop floor scheduling or lot-sizing, or their simple combinations such as scheduling with batching. Whereas many real-world production planning problems require the simultaneous solution of several problems (in addition to task scheduling and lot-sizing, the problems such as cutting, workforce scheduling, packing and transport issues), including the problems that are difficult to structure. The article presents examples and classification of production planning and scheduling systems in the foundry industry described in the literature, and also outlines the possible development directions of models and algorithms used in such systems

Evaluation of the Quality of the Free/Busy Car Park Information on the Basis of Certainty Factor of Hypothesis

The paper demonstrates an estimation method of the number of vacant parking spaces on the basis of video monitoring data. It provides a method for determining the quality of free/busy car park information using uncertainty modelling method based on certainty factor of hypothesis. The value of quality information IQ (CF) has been calculated with the help of a computer program. The simulation of results was performed depending on the input values change according to the normal distribution