Multiagent systems provide a powerful framework for developing real-time supervision and control systems for distributed and networked processes by automating adaptability and situation-dependent rearrangement of confidence to specific monitoring and diagnosis techniques. An agent-based framework for monitoring, analysis, diagnosis, and control with agent-based systems (MADCABS) is developed and tested by using detailed models of chemical reactor networks. MADCABS is composed of three main hierarchical layers, the physical communication layer, the supervision layer and the agent management layer. The supervision layer consists of agents and methods for data preprocessing, process monitoring, fault diagnosis, and control. The agent management layer conducts the assessment of agent performances to assign the priorities for selecting the most useful methods of process supervision for specific types of situations. MADCABS provides an excellent environment to assess the performance of various SPM and fault detection methods for specific regions of process operation and adapt the reliability to different techniques based on prior experience and recursive assessment of performances. The agent management layer offers the tools and metrics to assess the performance of the monitoring, detection and diagnosis tools and dynamically update the confidence to specific techniques in a context-dependent way. The paper illustrates the operation of MADCABS for monitoring and fault detection.