Harmonization and Integration with Knowledge Tools Clause Samples

Harmonization and Integration with Knowledge Tools. ‌ Any self-adaptive system running in a highly dynamic environment requires two types of knowledge: (i) the former to understand that the situation around calls for adaptation; (ii) the latter to understand which mechanisms of adaptation best suit such situation. In this context, WP3 and WP4 are focusing on different, yet complementary, perspectives. While WP3 is looking for knowledge models suitable for supporting reasoning and self-adaptation within highly dynamic environments, WP4 is experimenting with models, schemes, and mechanisms via which self-adaptation can be expressed. The ultimate goal of both WPs is to provide a sound set of conceptual and practical guidelines and tools to assist developers in modeling, engineering and implementing self-adaptive systems. In this section we summarize the efforts performed so far to ensure that the results of both WPs can be effectively integrated and harmonized into a coherent picture. In general, WP4 defines SCs as context-dependent components, as from Figure 4. From the in- ternal viewpoint, one can consider “Actions” (A1, A2, . . . , An) internal to the component that are selected by a “logic” module capable of identifying the most appropriate one given a specific situa- tion. Basic SCs can be specialized in goal-oriented SCs (see Figure 7) able to choose a chain of actions by considering both the goal of the component and the current situation. Goal-oriented SCs have been designed to cope with uncertainty by continuously learning from their previous actions. It is worth noticing that “logic” block can be externalized to another class of components called Autonomic Managers (AMs). These components continuously monitor SCs in terms of both internal and environmental state and provide suggestions about the most proper chain of actions to be executed. More specifically, AMs have been introduced to eventually separate SCs (i.e., components capable of taking actions) from their internal logic (i.e., the dynamic mapping between actions, operating condi- tions and components goals). This perspective introduces results achieved within WP3. KnowLang, in fact, has been specifically designed to cope with this task (see Figure 8). In KnowLang the autonomic self-adaptive behavior is provided by policies, events, actions, situa- tions, and relations between policies and situations. Policies are specified to handle specific situations and exhibit a behavior via actions generated in the environment or in the system itself. ...