Planning systems must handle uncertainty and change. Two fundamental approaches exist: Conditional Planning and Continuous Planning. Conditional planning creates pre-defined branches for known contingencies, like if condition X occurs, follow path A, if condition Y occurs, follow path B. This approach anticipates specific uncertainties and builds alternative paths into the plan.
Conditional planning works by identifying specific uncertainties and creating predetermined branches to handle each scenario. For example, when planning an event, we might create two paths: if the weather is sunny, hold it outdoors; if rainy, move it indoors. The key is that these contingencies are identified and planned for in advance, creating a structured if-then-else approach to handle known variables.
Continuous planning is a dynamic process where planning doesn't stop once execution begins. The system constantly monitors the environment, assesses the current state, and modifies the plan based on real-time feedback. Unlike conditional planning which handles pre-defined scenarios, continuous planning adapts to any change, whether foreseen or unexpected. This creates a continuous cycle of plan, execute, monitor, and adapt.
The key differences between these approaches are fundamental. Conditional planning focuses on pre-defined contingencies with branches created before execution, suitable when key uncertainties are known and enumerable. It has a static tree-like structure. Continuous planning focuses on ongoing adaptation throughout execution, essential in highly dynamic and unpredictable environments. It involves replanning during execution and can handle any change, whether foreseen or unforeseen, with a dynamic cyclical structure.
Each planning approach has specific applications. Conditional planning works best for scenarios with known risk factors and limited uncertainty types, such as resource allocation and emergency response protocols. Continuous planning excels in dynamic environments like autonomous vehicle navigation and real-time trading systems. In practice, both approaches can be combined to create robust planning systems that handle both anticipated and unexpected changes effectively.