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Download e-book for kindle: Active Conceptual Modeling of Learning: Next Generation by Peter P. Chen, Leah Y. Wong

By Peter P. Chen, Leah Y. Wong

This quantity features a choice of the papers provided in the course of the First foreign ACM-L Workshop, which was once held in Tucson, Arizona, in the course of the twenty fifth foreign convention on Conceptual Modeling, ER 2006.

Included during this cutting-edge survey are eleven revised complete papers, rigorously reviewed and chosen from the workshop displays. those are crowned off with four invited lectures and an introductory and motivational overview.

Taken as a complete, those papers conceal nearly the entire present pondering in conceptual modeling research.

The workshop in query all in favour of bettering the elemental knowing of ways to version continuous studying from earlier reviews and the way to seize wisdom from transitions among process states.

Active conceptual modeling is a continuous technique of describing all features of a site, its actions, and adjustments from diverse views according to our wisdom and understanding.

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Extra info for Active Conceptual Modeling of Learning: Next Generation Learning-Base System Development

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With minor modifications to the definition of models we could assume that rules by default are processed each time we get into an empty sequence of actions (so that rules will be processed at least at the end of a given transaction) in addition to the explicit processing points. Furthermore, we can put a restriction on a syntax which will require that every sequence of actions must end with a ↑ symbol – denoting special processing points. The hypothetical reasoning about the behavior of the system is based on the simple query language which consists of the statements of the following form: l after α at < Φ, Σ > (7) where l is either a fact or an event literal, α a sequence of actions, and < Φ, Σ > a state of facts and events.

44 G. Trajcevski and P. Scheuermann visual textual Action_1 precedes Action_2 Action_1 precedes Action_3 ..... Action_2 Action_1 Action_1 causes f1 Action_1 induces e1 Action_3 causes ..... " Fig. 6. Hypothetical Reasoning An important component of our envisioned system is the reality-aware simulator. This module serves the purpose of answering the users queries while minimizing the access to the actual reality modelled by the system. In particular, Figure 6 illustrates a scenario in which the user is interested in the energy-map in the region R of a given sensor network.

2. The Else-If parts at each level of nesting of the triggers correspond to alternative policies, based on the value of the respective conditions, once an instance of 34 G. Trajcevski and P. Scheuermann Trigger for Rq2: MovingToward event detected parent ON E_MovingTowards(O,’R’,5,T) IF JetsCount(’B1’,X,T1) AND X < 10 AND T1>=T within_event(E_MovingTowards(O,’R’,T1)) THEN ALERT(’b’,’A1’) Span child Distance event detected Consumed-by-Parent = no, Consume-Parent = no ON E_Distance(O,’R’,3,T2) IF Distance(’Marines’,’R’,X,T2) AND T2>T AND X>=5 THEN ALERT(’a’,’I1’,T2) No longer MovingTowards (zig-zag route) but still within Distance Fig.

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