We consider the following windy maze, where the wind condition is defined in the above: 0 The cost of one step for the agent is defined as follows: 1 for moving along the wind direction; 3 for moving against the wind direction; 2 for moving with the side wind cases. We assume that the square labeled with O is the starting square and the top right is the goal square and all shaded squares are obstacles. We use a label we did in class to indicates the order of choosing the corresponding unlabeled square and adding it to the frontier. To break tier for unlabeled squares (expanding children nodes), use this order: first westward; then northward; then eastward; then southward. To break tier for labeled squares (picking one child node to expand), the smallest label is picked first. Follow the same way as done in the class to show the search steps with labels (plus subscript numbers if needed) for the following search algorithms: 1. Uniform-Cost-Search (UCS) 2. Greedy Best-First Search (GBFS): We use a modified Manhattan distance used in class as the heuristic function h(n) by considering the windy situation as we did in HW1. Copy the above maze and paste it for each algorithm in the following form. If you can't copy the black square, you can put "#" inside instead. Fill the correct labels for each algorithm. We consider the following windy maze, where the wind condition is defined in the above: 0 The cost of one step for the agent is defined as follows: 1 for moving along the wind direction; 3 for moving against the wind direction; 2 for moving with the side wind cases. We assume that the square labeled with O is the starting square and the top right is the goal square and all shaded squares are obstacles. We use a label we did in class to indicates the order of choosing the corresponding unlabeled square and adding it to the frontier. To break tier for unlabeled squares (expanding children nodes), use this order: first westward; then northward; then eastward; then southward. To break tier for labeled squares (picking one child node to expand), the smallest label is picked first. Follow the same way as done in the class to show the search steps with labels (plus subscript numbers if needed) for the following search algorithms: 1. Uniform-Cost-Search (UCS) 2. Greedy Best-First Search (GBFS): We use a modified Manhattan distance used in class as the heuristic function h(n) by considering the windy situation as we did in HW1. Copy the above maze and paste it for each algorithm in the following form. If you can't copy the black square, you can put "#" inside instead. Fill the correct labels for each algorithm
