Date of Award:
Doctor of Philosophy (PhD)
Biological and Irrigation Engineering
Gary P. Merkley
Gary P. Merkley
Christopher M.U. Neale
A modern computer-based simulation tool (WaterMan) in the form of a game for on-farm water management was developed for application in training events for farmers, students, and irrigators. The WaterMan game utilizes an interactive framework, thereby allowing the user to develop scenarios and test alternatives in a convenient, risk-free environment. It includes a comprehensive soil water and salt balance calculation algorithm. It also employs heuristic capabilities for modeling all of the important aspects of on-farm water management, and to provide reasonable scores and advice to the trainees.
Random events (both favorable and unfavorable) and different strategic decisions are included in the game for more realism and to provide an appropriate level of challenge according to player performance. Thus, the ability to anticipate the player skill level, and to reply with random events appropriate to the anticipated level, is provided by the heuristic capabilities used in the software. These heuristic features were developed based on a combination of two artificial intelligence approaches: (1) a pattern recognition approach; and (2) reinforcement learning based on a Markov Decision Processes approach, specifically, the Q-learning method. These two approaches were combined in a new way to account for the difference in the effect of actions taken by the player and action taken by the system on the game world. The reward function for the Q-learning method was modified to reflect the anticipated type of the WaterMan game as what is referred to as a partially competitive and partially cooperative game.
Twenty-two different persons classified under three major categories (1) practicing farmers; (2) persons without an irrigation background; and (3) persons with an irrigation background, were observed while playing the game, and each of them filled out a questionnaire about the game. The technical module of the game was validated in two ways: through conducting mass balance calculations for soil water content and salt content over a period of simulation time, and through comparing the WaterMan technical module output data in calculating the irrigation requirements and the use of irrigation scheduling recommendations with those obtained from the same set of input data to the FAO CropWat 8 software. The testing results and the technical validation outcomes demonstrate the high performance of the WaterMan game as a heuristic training tool for on-farm water management.
Shaban, Mohammed Z., "On-Farm Water Management Game With Heuristic Capabilities" (2012). All Graduate Theses and Dissertations. 1255.
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