The ability for software systems to self-diagnose and self-adjust is highly desirable in military and civilian applications in the cyber domain. The capability of automatic adaptive reasoning and monitoring is the first step towards this objective. To address this, IAI has been awarded a new contract entitled “SAM: A Self Adaptive System Monitoring Architecture Multi-Abstractions System Reasoning Infrastructure toward Achieving Adaptive Computing System.” IAI’s in-house machine learning framework, ABMiner, and ontological knowledge representation workbench, ALARM, will be leveraged to develop a self-adaptive monitoring architecture, called SAM, as the system reasoning infrastructure for adaptive computing system. The conceptual architecture of SAM has a data mining component, a multi-feature monitoring model, an ontological knowledge representation, and a human expert and data acquisition controller. The human expert supervises the execution of the monitoring system, and defines the features used by data mining to set up the multi-feature monitoring model for the application program. This model is used during runtime to detect any abnormal behavior of the application based on the multi-abstracted features. ABMiner allows the use of various machine learning techniques, including ensembles, to select the most significant semantic features to characterize the monitored application. IAI’s work on ontological knowledge representation techniques will be leveraged to represent the execution of an application program in an understandable way to enable human experts to adjust the automatic reasoning system iteratively. Finally, the proposed techniques will be integrated in a workable self-adaptive monitoring prototype that checks the execution of dynamically evolving applications. SAM has many uses in application protection, software characterization, and self-adaptive and self-healing computing systems.