Strategic AI: Iterative Deepening A for Real-Time Challenges
Rekha R Nair, Kishore S, Shalini Joseph, Rashmi Hegde K, Rahul Kumar Thakur · 2025
The Iterative Deepening A* (IDA*) is a robust solution for tackling complex problems in vast state spaces because it combines the memory efficiency of depth-first search with the optimality of A*. The application of IDA in real-time strategy games is explored in this paper. Computational inefficiency and memory limitations are problems for traditional A* algorithms. This study introduces a novel framework for IDA that can respond to real-time changes, such as evolving terrains and resource availability. Parallel processing is used to partition the search space, which reduces computation time while maintaining accuracy. Improved path-finding efficiency and enhanced resource management capabilities are shown to be compatible with IDA*. This research extends the applicability of IDA to real-time and provides a foundation for further innovations in the field of artificial intelligence.