By Ronny Hartanto

ISBN-10: 3642225799

ISBN-13: 9783642225796

The Hybrid Deliberative Layer (HDL) solves the matter that an clever agent faces in facing a large number of info that can or is probably not worthwhile in producing a plan to accomplish a objective. the knowledge, that an agent may have, is bought and kept within the DL version. hence, the HDL is used because the major wisdom base method for the agent.

In this paintings, a unique technique which amalgamates Description common sense (DL) reasoning with Hierarchical activity community (HTN) making plans is brought. An research of the functionality of the method has been carried out and the implications express that this procedure yields considerably smaller making plans challenge descriptions than these generated through present representations in HTN planning.

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Sample text

Its name is taken from the syllable of the world encyclopedia. microworlds is related to the bottom up approach, that is usually practised by programmers, while the Cyc categories are related to the top down approach, that is usually followed by philosophers. dl defines knowledge in two fractions, namely TBox and ABox . Hence, the planning domain needs to be modelled in these fractions as well. 8 depicts two ABoxes and two TBoxes for representing planning knowledge in dl representation. The first pair of TBox and ABox represent the htn planning ontologies while the other pair represent the states of the planning problem that are needed by the htn planner.

This work presents a novel approach, that combines a dl reasoner and an htn planner into a coherent system, to be used in the robotics domain. 1). The reasoning capability of dl reasoners provides valuable advantages to the htn planner. The user now has additional leverage to customise the planning problem such that an intractable planning problem is avoided. The hdl system increases the reusability of any existing planning domain in its model and facilitates the use of the planning system for non-planning expert users.

It is based on semantic networks and frame systems. , expressions that are built from atomic concepts (unary predicates) and atomic roles (binary predicates) using the concept and role constructors provided by the particular dl; on the other hand, dls differ from their predecessors, such as semantic networks and frames, in that they are equipped with a formal, logic-based semantics. dl can be categorised a mature knowledge representation. [62] describes the development of dl through four distinct phases: • Phase 0 (1965-1980) is the pre-dl phase.

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A Hybrid Deliberative Layer for Robotic Agents: Fusing DL Reasoning with HTN Planning in Autonomous Robots by Ronny Hartanto


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