Update to include test code, realize issues, and clean up unnecessary…

… files
aimacode · carwyn987 · Sep 25, 2025 · Sep 27, 2025 · Sep 27, 2025 · Sep 27, 2025
commit a1090c0981cd05451f83b9a9e62a790f346c7ec4
diff --git a/linearize.py b/linearize.py
@@ -0,0 +1,108 @@
+
+class Linearize:
+
+    def __init__(self, planning_problem):
+        self.planning_problem = planning_problem
+
+    def filter(self, solution):
+        """Filter out persistence actions from a solution"""
+
+        new_solution = []
+        for section in solution[0]:
+            new_section = []
+            for operation in section:
+                if not (operation.op[0] == 'P' and operation.op[1].isupper()):
+                    new_section.append(operation)
+            new_solution.append(new_section)
+        return new_solution
+
+    def orderlevel(self, level, planning_problem):
+        """Return valid linear order of actions for a given level"""
+
+        for permutation in itertools.permutations(level):
+            print(f"TRYING PARTIAL PLAN: {permutation}")  ## Bill's hack                
+            temp = copy.deepcopy(planning_problem)
+            count = 0
+            ## print(f"PERMUTATION: {permutation}")  ## Bill's hack
+            for action in permutation:
+                try:
+                    # print(f"TRY ACTION: {action}")  ## Bill's hack
+                    temp.act(action)
+                    count += 1
+                    # print(f"TRY ACTION: {action} SUCCESS!")  ## Bill's hack
+                except:
+                    # print(f"TRY ACTION: {action} FAIL!")  ## Bill's hack
+                    count = 0
+                    temp = copy.deepcopy(planning_problem)
+                    continue     ##break
+            if count == len(permutation):
+                print(f"\nSUCCESSFUL PARTIAL PLAN ORDERING: {permutation}")  ## Bill's hack
+                return list(permutation), temp
+        print(f"NO SUCCESSFUL PARTIAL PLAN: {level}")  ## Bill's hack                
+        return None, planning_problem  ## added planning_problem... its gotta return a planning problem and start over if it fails, but maybe this is saying return fail and the unsolved planning problem
+
+    def execute(self):
+        """Finds total-order solution for a planning graph"""
+
+        graphPlan_solution = GraphPlan(self.planning_problem).execute()
+
+        ## Bill's stuff from playing around
+        ## print(f"UNFILTERED PLAN: {graphPlan_solution}")  ## Bill's hack
+        ## pnl(graphPlan_solution)
+        ## for possible_plan in graphPlan_solution:
+        ##    possible_plan = [possible_plan]
+        ##    filtered_possible_plan = self.filter(possible_plan)
+        ##    print(f"POSSIBLE PLAN: {filtered_possible_plan}")  ## Bill's hack
+        ## flattened_graphplan = self.filter(graphPlan_solution)
+        ## flattened_graphplan = sum(graphPlan_solution, [])  ## Bill's hack
+        ## flattened_graphplan = sum(flattened_graphplan, [])  ## Bill's hack
+        ##  flattened_graphplan = [flattened_graphplan]
+        ## graphPlan_solution = [flattened_graphplan]  ## Bill's hack
+        ##  pnl(flattened_graphplan)
+
+        ## I think I have to go over all permutations of possbile partial graphplans
+
+        for possible_plan in itertools.permutations(graphPlan_solution):   ## Bill's hack
+
+            ## possible_plan = [possible_plan]  ## Bill's hack, stuff below expect a list with one element which is also a list
+            ## filtered_solution = self.filter(graphPlan_solution)   # original
+
+            filtered_solution = self.filter(possible_plan)   # my mod
+
+            print(f"TRYING FILTERED PLAN: {filtered_solution}")  ## Bill's hack
+
+            ## filtered_solution = self.filter(possible_plan)  # mod
+            ## print(f"\nFILTERED PLAN: {filtered_solution}")  ## Bill's hack
+            ## pnl(filtered_solution)
+            ## filtered_solution = possible_plan
+
+            ordered_solution = []
+            planning_problem = self.planning_problem
+            for level in filtered_solution:
+
+                ## print(f"TRYING SOLUTION LEVEL: {level}")  ## Bill's hack
+
+                ## the below is a key line, the key line
+                level_solution, planning_problem = self.orderlevel(level, planning_problem)  ## actions get applied
+                if not level_solution:  # This checks if level_solution is None or an empty list
+                    print(f"PLAN FAIL: {filtered_solution}")  ## Bill's hack
+                    continue   ## Bill's hack!!  if empty, continue looking.  
+
+                print(f"LEVEL SOLUTION: {level_solution}")  ## Bill's hack
+                ##print(f"CURRENT STATE: {planning_problem.initial}\n")  ## Bill's hack                
+                ## for action in level_solution:
+                ##    print(f"APPLY ACTION: {action}")  ## Bill's hack                    
+                ##    planning_problem.act(action)           # complete guess, apply action to the problem and keep going
+
+                ## I think we need to apply the plan to the planning problem and modify it
+                for element in level_solution:   
+                    ordered_solution.append(element)
+
+            if not ordered_solution:
+                continue  ## no plan possible from the partial plan at the level
+            else:
+                print(f"WORKING SOL'N: {ordered_solution}")  ## Bill's hack
+                break
+
+        return ordered_solution
+
diff --git a/logistics-test-probs.py b/logistics-test-probs.py
@@ -0,0 +1,46 @@
+
+
+##    initial_state = 'In(C1, R1) & In(C2, D1) & In(C3, D2) & In(R1, D1) & Holding(R1)'
+
+logisticsPlan('In(C1, D1)')
+
+logisticsPlan('In(C1,D2)')
+
+logisticsPlan('In(C1, D1) & In(R1, D2)')
+logisticsPlan('In(R1, D2) & In(C1, D1)')
+
+logisticsPlan('In(C1, D1) & In(C3, R1)')
+logisticsPlan('In(C1, D1) & In(C3, R1) & In(R1, D3)')
+
+logisticsPlan('In(C1, D1) & In(R1, D3) & In(C3, R1)')
+logisticsPlan('In(C1, D1) & In(C3, D3)')
+
+logisticsPlan('In(C1, D1) & In(R1, D2) & In(C3, R1)')
+
+logisticsPlan('In(C1, D1) & In(C3, R1) & In(R1, D3)')
+
+logisticsPlan('In(C1, D1) & In(C2, D3)')
+
+
+logisticsPlan('In(C3, D1)')
+
+logisticsPlan('In(C2, D3)')
+
+logisticsPlan('In(C3, D3)')
+
+
+#no plans for these below
+logisticsPlan('In(C2, D3) & In(C3, D3)')
+
+logisticsPlan('In(C3, D3) & In(C2, D3)')
+
+logisticsPlan('In(C1, D2) & In(C3, D3)')
+
+logisticsPlan('In(C1, D3) & In(C2, D3) & In(C3, D3)')  ## homework??
+
+logisticsPlan('In(C1, D2) & In(C3, D3) & In(C2, D1)')
+
+
+#kaboom... didn't stop?
+logisticsPlan('In(C1, D2) & In(C3, D3) & In(C2, D3) & In(R1, D1)')
+
diff --git a/.coveragerc → other_shit_idgafabout/.coveragerc b/.coveragerc → other_shit_idgafabout/.coveragerc
diff --git a/.flake8 → other_shit_idgafabout/.flake8 b/.flake8 → other_shit_idgafabout/.flake8
diff --git a/CONTRIBUTING.md → other_shit_idgafabout/CONTRIBUTING.md b/CONTRIBUTING.md → other_shit_idgafabout/CONTRIBUTING.md
diff --git a/LICENSE → other_shit_idgafabout/LICENSE b/LICENSE → other_shit_idgafabout/LICENSE
diff --git a/SUBMODULE.md → other_shit_idgafabout/SUBMODULE.md b/SUBMODULE.md → other_shit_idgafabout/SUBMODULE.md
diff --git a/agents.ipynb → other_shit_idgafabout/agents.ipynb b/agents.ipynb → other_shit_idgafabout/agents.ipynb
diff --git a/agents4e.py → other_shit_idgafabout/agents4e.py b/agents4e.py → other_shit_idgafabout/agents4e.py
diff --git a/other_shit_idgafabout/aima_8puzzle.py b/other_shit_idgafabout/aima_8puzzle.py
@@ -0,0 +1,21 @@
+"""
+Demo for A* with EightPuzzle
+For use with the AIMA codebase: https://github.com/aimacode/aima-python
+CMSC 421 - Fall 2025
+"""
+from time import time
+from search import EightPuzzle, astar_search
+
+# INITIAL_STATE = (1, 2, 3, 4, 5, 6, 7, 8, 0) # already solved
+INITIAL_STATE = (1, 2, 3, 4, 5, 6, 7, 0, 8) # just one swap to solve
+# INITIAL_STATE = (1, 2, 3, 4, 0, 6, 7, 5, 8) # just two swaps to solve
+# INITIAL_STATE = (1, 2, 3, 0, 4, 6, 7, 5, 8) # just three swaps to solve
+# INITIAL_STATE = (8, 3, 2, 4, 5, 7, 1, 6, 0) # more complex initial state
+
+EP = EightPuzzle(INITIAL_STATE)
+print('Initial State: ' + str(INITIAL_STATE))
+print('Initial State solvable: ' + str(EP.check_solvability(INITIAL_STATE)))
+print('Running A*...')
+t0 = time()
+astar_search(EP, display=True)
+print('Solved in %f seconds'%(time()-t0))
diff --git a/other_shit_idgafabout/aima_my_tsp.py b/other_shit_idgafabout/aima_my_tsp.py
@@ -0,0 +1,93 @@
+"""
+Code skeleton for A* with TSP
+For use with the AIMA codebase: https://github.com/aimacode/aima-python
+CMSC 421 - Fall 2025
+"""
+from time import time
+import numpy as np
+from search import Problem, astar_search
+from scipy.sparse import csgraph
+
+### Define TSP ###
+
+class MyTSP(Problem):
+
+    # NOTE: This is just a suggestion for setting up your __init__,
+    # you can use any design you want
+    def __init__(self, weights, initial=(0,), goal=None):   
+        super().__init__(initial, goal)
+        self.weights = weights
+        self.num_cities = weights.shape[0]
+        self.cities = list(range(0, self.num_cities))
+
+    def actions(self, state):
+        """Return the actions that can be executed in the given
+        state. The result would typically be a list, but if there are
+        many actions, consider yielding them one at a time in an
+        iterator, rather than building them all at once."""
+        raise NotImplementedError
+        # TODO: your code here
+
+    # NOTE: If you make your state a list object, you'll wind
+    # up with an error like this: TypeError: unhashable type: 'list'
+    # One work-around is the make your states tuples instead.
+    def result(self, state, action):
+        """Return the state that results from executing the given
+        action in the given state. The action must be one of
+        self.actions(state)."""
+        raise NotImplementedError
+        # TODO: your code here
+
+    def goal_test(self, state):
+        """Return True if the state is a goal. The default method compares the
+        state to self.goal or checks for state in self.goal if it is a
+        list, as specified in the constructor. Override this method if
+        checking against a single self.goal is not enough."""
+        raise NotImplementedError
+        # TODO: your code here
+
+    # NOTE: Remember the full cost includes the round trip back to the starting city!
+    # So if you are adding the final city to the path, you should also add the cost
+    # for the final edge too.
+    def path_cost(self, c, state1, action, state2):
+        """Return the cost of a solution path that arrives at state2 from
+        state1 via action, assuming cost c to get up to state1. If the problem
+        is such that the path doesn't matter, this function will only look at
+        state2. If the path does matter, it will consider c and maybe state1
+        and action. The default method costs 1 for every step in the path."""
+        raise NotImplementedError
+        # TODO: your code here
+
+    def value(self, state):
+        """For optimization problems, each state has a value. Hill Climbing
+        and related algorithms try to maximize this value."""
+        raise NotImplementedError
+        # TODO: your code here
+
+    # NOTE: For debugging purposes, you can use h(n)=0 while writing and testing
+    # the rest of your code
+    def h(self, node):
+        """Return the heuristic value for a given state. astar_search will
+        look for this heuristic function when run."""
+        raise NotImplementedError        
+        # TODO: your code here
+
+### Run A* ###
+
+# NOTE: select a weight matrix to load, depending on where you unzipped them
+MATRIX_FILE = '/home/carwyn/dev/phd/ta/aima/aima-python/aima-data/mats_911/5_random_adj_mat_0.txt'
+
+MAT = np.loadtxt(MATRIX_FILE)
+print('Loaded road cost matrix:')
+print(MAT)
+MTSP = MyTSP(MAT)
+
+print('Running A*...')
+t0 = time()
+tsp_sol = astar_search(MTSP, display=True)
+print('Solved in %f seconds'%(time()-t0))
+
+tsp_sol = tsp_sol.state
+print('Solution Path: ' + str(tsp_sol))
+sol_cost = MTSP.value(tsp_sol)
+print('Solution Cost: ' + str(sol_cost))
diff --git a/arc_consistency_heuristics.ipynb → ...gafabout/arc_consistency_heuristics.ipynb b/arc_consistency_heuristics.ipynb → ...gafabout/arc_consistency_heuristics.ipynb
diff --git a/csp.ipynb → other_shit_idgafabout/csp.ipynb b/csp.ipynb → other_shit_idgafabout/csp.ipynb
diff --git a/deep_learning4e.py → other_shit_idgafabout/deep_learning4e.py b/deep_learning4e.py → other_shit_idgafabout/deep_learning4e.py
diff --git a/games.ipynb → other_shit_idgafabout/games.ipynb b/games.ipynb → other_shit_idgafabout/games.ipynb
diff --git a/games.py → other_shit_idgafabout/games.py b/games.py → other_shit_idgafabout/games.py
diff --git a/games4e.ipynb → other_shit_idgafabout/games4e.ipynb b/games4e.ipynb → other_shit_idgafabout/games4e.ipynb
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diff --git a/index.ipynb → other_shit_idgafabout/index.ipynb b/index.ipynb → other_shit_idgafabout/index.ipynb
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diff --git a/ipyviews.py → other_shit_idgafabout/ipyviews.py b/ipyviews.py → other_shit_idgafabout/ipyviews.py
diff --git a/js/canvas.js → other_shit_idgafabout/js/canvas.js b/js/canvas.js → other_shit_idgafabout/js/canvas.js
diff --git a/js/continuousworld.js → other_shit_idgafabout/js/continuousworld.js b/js/continuousworld.js → other_shit_idgafabout/js/continuousworld.js
diff --git a/js/gridworld.js → other_shit_idgafabout/js/gridworld.js b/js/gridworld.js → other_shit_idgafabout/js/gridworld.js
diff --git a/knowledge.py → other_shit_idgafabout/knowledge.py b/knowledge.py → other_shit_idgafabout/knowledge.py
diff --git a/knowledge_FOIL.ipynb → other_shit_idgafabout/knowledge_FOIL.ipynb b/knowledge_FOIL.ipynb → other_shit_idgafabout/knowledge_FOIL.ipynb
diff --git a/knowledge_current_best.ipynb → ...t_idgafabout/knowledge_current_best.ipynb b/knowledge_current_best.ipynb → ...t_idgafabout/knowledge_current_best.ipynb
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diff --git a/learning.ipynb → other_shit_idgafabout/learning.ipynb b/learning.ipynb → other_shit_idgafabout/learning.ipynb
diff --git a/learning.py → other_shit_idgafabout/learning.py b/learning.py → other_shit_idgafabout/learning.py
diff --git a/learning4e.py → other_shit_idgafabout/learning4e.py b/learning4e.py → other_shit_idgafabout/learning4e.py
diff --git a/learning_apps.ipynb → other_shit_idgafabout/learning_apps.ipynb b/learning_apps.ipynb → other_shit_idgafabout/learning_apps.ipynb
diff --git a/making_simple_decision4e.py → ...it_idgafabout/making_simple_decision4e.py b/making_simple_decision4e.py → ...it_idgafabout/making_simple_decision4e.py
diff --git a/mdp.ipynb → other_shit_idgafabout/mdp.ipynb b/mdp.ipynb → other_shit_idgafabout/mdp.ipynb
diff --git a/mdp.py → other_shit_idgafabout/mdp.py b/mdp.py → other_shit_idgafabout/mdp.py
diff --git a/mdp4e.py → other_shit_idgafabout/mdp4e.py b/mdp4e.py → other_shit_idgafabout/mdp4e.py
diff --git a/mdp_apps.ipynb → other_shit_idgafabout/mdp_apps.ipynb b/mdp_apps.ipynb → other_shit_idgafabout/mdp_apps.ipynb
diff --git a/neural_nets.ipynb → other_shit_idgafabout/neural_nets.ipynb b/neural_nets.ipynb → other_shit_idgafabout/neural_nets.ipynb
diff --git a/nlp.ipynb → other_shit_idgafabout/nlp.ipynb b/nlp.ipynb → other_shit_idgafabout/nlp.ipynb
diff --git a/nlp.py → other_shit_idgafabout/nlp.py b/nlp.py → other_shit_idgafabout/nlp.py
diff --git a/nlp4e.py → other_shit_idgafabout/nlp4e.py b/nlp4e.py → other_shit_idgafabout/nlp4e.py
diff --git a/nlp_apps.ipynb → other_shit_idgafabout/nlp_apps.ipynb b/nlp_apps.ipynb → other_shit_idgafabout/nlp_apps.ipynb
diff --git a/notebook.py → other_shit_idgafabout/notebook.py b/notebook.py → other_shit_idgafabout/notebook.py
diff --git a/notebook4e.py → other_shit_idgafabout/notebook4e.py b/notebook4e.py → other_shit_idgafabout/notebook4e.py
diff --git a/notebooks/chapter19/Learners.ipynb → ...fabout/notebooks/chapter19/Learners.ipynb b/notebooks/chapter19/Learners.ipynb → ...fabout/notebooks/chapter19/Learners.ipynb
diff --git a/...chapter19/Loss Functions and Layers.ipynb → ...chapter19/Loss Functions and Layers.ipynb b/...chapter19/Loss Functions and Layers.ipynb → ...chapter19/Loss Functions and Layers.ipynb
diff --git a/...ter19/Optimizer and Backpropagation.ipynb → ...ter19/Optimizer and Backpropagation.ipynb b/...ter19/Optimizer and Backpropagation.ipynb → ...ter19/Optimizer and Backpropagation.ipynb
diff --git a/notebooks/chapter19/RNN.ipynb → ..._idgafabout/notebooks/chapter19/RNN.ipynb b/notebooks/chapter19/RNN.ipynb → ..._idgafabout/notebooks/chapter19/RNN.ipynb
diff --git a/notebooks/chapter19/images/autoencoder.png → ...otebooks/chapter19/images/autoencoder.png b/notebooks/chapter19/images/autoencoder.png → ...otebooks/chapter19/images/autoencoder.png
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diff --git a/...s/chapter19/images/corss_entropy_plot.png → ...s/chapter19/images/corss_entropy_plot.png b/...s/chapter19/images/corss_entropy_plot.png → ...s/chapter19/images/corss_entropy_plot.png
diff --git a/notebooks/chapter19/images/mse_plot.png → ...t/notebooks/chapter19/images/mse_plot.png b/notebooks/chapter19/images/mse_plot.png → ...t/notebooks/chapter19/images/mse_plot.png
diff --git a/notebooks/chapter19/images/nn.png → ...afabout/notebooks/chapter19/images/nn.png b/notebooks/chapter19/images/nn.png → ...afabout/notebooks/chapter19/images/nn.png
diff --git a/notebooks/chapter19/images/nn_steps.png → ...t/notebooks/chapter19/images/nn_steps.png b/notebooks/chapter19/images/nn_steps.png → ...t/notebooks/chapter19/images/nn_steps.png
diff --git a/notebooks/chapter19/images/perceptron.png → ...notebooks/chapter19/images/perceptron.png b/notebooks/chapter19/images/perceptron.png → ...notebooks/chapter19/images/perceptron.png
diff --git a/...ooks/chapter19/images/rnn_connections.png → ...ooks/chapter19/images/rnn_connections.png b/...ooks/chapter19/images/rnn_connections.png → ...ooks/chapter19/images/rnn_connections.png
diff --git a/notebooks/chapter19/images/rnn_unit.png → ...t/notebooks/chapter19/images/rnn_unit.png b/notebooks/chapter19/images/rnn_unit.png → ...t/notebooks/chapter19/images/rnn_unit.png
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diff --git a/notebooks/chapter19/images/vanilla.png → ...ut/notebooks/chapter19/images/vanilla.png b/notebooks/chapter19/images/vanilla.png → ...ut/notebooks/chapter19/images/vanilla.png
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diff --git a/...er21/Passive Reinforcement Learning.ipynb → ...er21/Passive Reinforcement Learning.ipynb b/...er21/Passive Reinforcement Learning.ipynb → ...er21/Passive Reinforcement Learning.ipynb
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diff --git a/notebooks/chapter22/Grammar.ipynb → ...afabout/notebooks/chapter22/Grammar.ipynb b/notebooks/chapter22/Grammar.ipynb → ...afabout/notebooks/chapter22/Grammar.ipynb
diff --git a/notebooks/chapter22/Introduction.ipynb → ...ut/notebooks/chapter22/Introduction.ipynb b/notebooks/chapter22/Introduction.ipynb → ...ut/notebooks/chapter22/Introduction.ipynb
diff --git a/notebooks/chapter22/Parsing.ipynb → ...afabout/notebooks/chapter22/Parsing.ipynb b/notebooks/chapter22/Parsing.ipynb → ...afabout/notebooks/chapter22/Parsing.ipynb
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diff --git a/notebooks/chapter22/nlp_apps.ipynb → ...fabout/notebooks/chapter22/nlp_apps.ipynb b/notebooks/chapter22/nlp_apps.ipynb → ...fabout/notebooks/chapter22/nlp_apps.ipynb
diff --git a/...ooks/chapter24/Image Edge Detection.ipynb → ...ooks/chapter24/Image Edge Detection.ipynb b/...ooks/chapter24/Image Edge Detection.ipynb → ...ooks/chapter24/Image Edge Detection.ipynb
diff --git a/notebooks/chapter24/Image Segmentation.ipynb → ...ebooks/chapter24/Image Segmentation.ipynb b/notebooks/chapter24/Image Segmentation.ipynb → ...ebooks/chapter24/Image Segmentation.ipynb
diff --git a/notebooks/chapter24/Objects in Images.ipynb → ...tebooks/chapter24/Objects in Images.ipynb b/notebooks/chapter24/Objects in Images.ipynb → ...tebooks/chapter24/Objects in Images.ipynb
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