针对开放式环境下松耦合程度和可靠性不够的协作模式的缺点,以及协同制造装配问题出现的"结构失配"和"工艺革新"的特性,提出CRQA_(OVTM)Agent模型.模型从服务参数(属性)松耦合程度和服务执行结果确定性两个方面区别定义普通(O,Ordinary)接口、转换(V,con V ersion)接口、多参数适配器(T,multiparameteradap Tor)接口和概念实例调制器(M,conceptinstance M odulator)接口,并在此基础上提供包括普通协作、转换性协作、适配性协作和调制性协作的混合协作模式,且在处方的基础上引入量化合成,以更加灵活的方式处理"结构失配"和"工艺革新"问题.同时模型引入合同的约束,保证自组织协作是可信的.通过验证并与RPACT IAgent模型比较可知,该模型的协作机制既具有很高的成功率和效率,又具有很高的灵活性,更加适合开放环境下的协同制造装配.
As the tableau algorithm would produce a lot of description overlaps when judging the satisfiabilities of concepts（thus wasting much space）,a clause-based enhancing mode designed for the language ALCN is proposed.This enhancing mode constructs a disjunctive normal form on concept expressions and keeps only one conjunctive clause,and then substitutes the obtained succinctest conjunctive clause for sub-concepts set in the labeling of nodes of a completion tree constructed by the tableau algorithm （such a process may be repeated as many times as needed）.Due to the avoidance of tremendous descriptions redundancies caused by applying ∩- and ∪-rules of the ordinary tableau algorithm,this mode greatly improves the spatial performance as a result.An example is given to demonstrate the application of this enhancing mode and its reduction in the cost of space. Results show that the improvement is very outstanding.
