AI Search Methods Quiz 2: 2 April 2023, Set QPE2 (January 2023 term)

SEARCH
The figure shows a map with several locations on a grid where each tile is 1x1 in size. The locations are at grid points and are connected by two way edges (roads), where each edge has a cost that is the same in both directions. Observe that the edge costs are not necessarily proportional to the coordinate based distance estimates.
The start node is S and the goal node is G, the MoveGen function returns neighbours in alphabetical order. Use Manhattan distance as the heuristic function.
Tie-breaker: when several nodes have the same best cost, use alphabetical order to break ties.

SEARCH
The figure shows a map with several locations on a grid where each tile is 1x1 in size. The locations are at grid points and are connected by two way edges (roads), where each edge has a cost that is the same in both directions. Observe that the edge costs are not necessarily proportional to the coordinate based distance estimates.
The start node is S and the goal node is G, the MoveGen function returns neighbours in alphabetical order. Use Manhattan distance as the heuristic function.
Tie-breaker: when several nodes have the same best cost, use alphabetical order to break ties.

In the map, S is the first node to be refined, determine the next 4 nodes (from the 2nd to 5th node) refined by A*. Enter the nodes in the order they are refined.
Enter a comma separated list of node labels.
NO SPACES, TABS, DOTS, BRACKETS OR EXTRANEOUS CHARACTERS. Answer format: W,X,Y,Z

SEARCH
The figure shows a map with several locations on a grid where each tile is 1x1 in size. The locations are at grid points and are connected by two way edges (roads), where each edge has a cost that is the same in both directions. Observe that the edge costs are not necessarily proportional to the coordinate based distance estimates.
The start node is S and the goal node is G, the MoveGen function returns neighbours in alphabetical order. Use Manhattan distance as the heuristic function.
Tie-breaker: when several nodes have the same best cost, use alphabetical order to break ties.

SEARCH
The figure shows a map with several locations on a grid where each tile is 1x1 in size. The locations are at grid points and are connected by two way edges (roads), where each edge has a cost that is the same in both directions. Observe that the edge costs are not necessarily proportional to the coordinate based distance estimates.
The start node is S and the goal node is G, the MoveGen function returns neighbours in alphabetical order. Use Manhattan distance as the heuristic function.
Tie-breaker: when several nodes have the same best cost, use alphabetical order to break ties.

For the 4 nodes from the 2nd to 5th node, list the f-values of those nodes as a comma separated list.
Enter a comma separated list of natural numbers. NO SPACES, TABS, DOTS, BRACKETS OR EXTRANEOUS CHARACTERS. Answer format: 2,7,1,8

SEARCH
The figure shows a map with several locations on a grid where each tile is 1x1 in size. The locations are at grid points and are connected by two way edges (roads), where each edge has a cost that is the same in both directions. Observe that the edge costs are not necessarily proportional to the coordinate based distance estimates.
The start node is S and the goal node is G, the MoveGen function returns neighbours in alphabetical order. Use Manhattan distance as the heuristic function.
Tie-breaker: when several nodes have the same best cost, use alphabetical order to break ties.

SEARCH
The figure shows a map with several locations on a grid where each tile is 1x1 in size. The locations are at grid points and are connected by two way edges (roads), where each edge has a cost that is the same in both directions. Observe that the edge costs are not necessarily proportional to the coordinate based distance estimates.
The start node is S and the goal node is G, the MoveGen function returns neighbours in alphabetical order. Use Manhattan distance as the heuristic function.
Tie-breaker: when several nodes have the same best cost, use alphabetical order to break ties.

For the 4 nodes from the 2nd to 5th node, list the parent nodes assigned by A*.
Enter a comma separated list of parent node labels. NO SPACES, TABS, DOTS, BRACKETS OR EXTRANEOUS CHARACTERS. Answer format: W,X,Y,Z

SEARCH
The figure shows a map with several locations on a grid where each tile is 1x1 in size. The locations are at grid points and are connected by two way edges (roads), where each edge has a cost that is the same in both directions. Observe that the edge costs are not necessarily proportional to the coordinate based distance estimates.
The start node is S and the goal node is G, the MoveGen function returns neighbours in alphabetical order. Use Manhattan distance as the heuristic function.
Tie-breaker: when several nodes have the same best cost, use alphabetical order to break ties.

SEARCH
The figure shows a map with several locations on a grid where each tile is 1x1 in size. The locations are at grid points and are connected by two way edges (roads), where each edge has a cost that is the same in both directions. Observe that the edge costs are not necessarily proportional to the coordinate based distance estimates.
The start node is S and the goal node is G, the MoveGen function returns neighbours in alphabetical order. Use Manhattan distance as the heuristic function.
Tie-breaker: when several nodes have the same best cost, use alphabetical order to break ties.

What is the final path found by A*?
Enter the path as a comma separated list. NO SPACES, TABS, DOTS, BRACKETS OR EXTRANEOUS CHARACTERS. Answer format: S,X,Y,Z,G

SEARCH
The figure shows a map with several locations on a grid where each tile is 1x1 in size. The locations are at grid points and are connected by two way edges (roads), where each edge has a cost that is the same in both directions. Observe that the edge costs are not necessarily proportional to the coordinate based distance estimates.
The start node is S and the goal node is G, the MoveGen function returns neighbours in alphabetical order. Use Manhattan distance as the heuristic function.
Tie-breaker: when several nodes have the same best cost, use alphabetical order to break ties.

SEARCH
The figure shows a map with several locations on a grid where each tile is 1x1 in size. The locations are at grid points and are connected by two way edges (roads), where each edge has a cost that is the same in both directions. Observe that the edge costs are not necessarily proportional to the coordinate based distance estimates.
The start node is S and the goal node is G, the MoveGen function returns neighbours in alphabetical order. Use Manhattan distance as the heuristic function.
Tie-breaker: when several nodes have the same best cost, use alphabetical order to break ties.

For w=2, what is the final path found by WA* algorithm?
Enter the path as a comma separated list. NO SPACES, TABS, DOTS, BRACKETS OR EXTRANEOUS CHARACTERS. Answer format: S,X,Y,Z,G

SEARCH
The figure shows a map with several locations on a grid where each tile is 1x1 in size. The locations are at grid points and are connected by two way edges (roads), where each edge has a cost that is the same in both directions. Observe that the edge costs are not necessarily proportional to the coordinate based distance estimates.
The start node is S and the goal node is G, the MoveGen function returns neighbours in alphabetical order. Use Manhattan distance as the heuristic function.
Tie-breaker: when several nodes have the same best cost, use alphabetical order to break ties.

SEARCH
The figure shows a map with several locations on a grid where each tile is 1x1 in size. The locations are at grid points and are connected by two way edges (roads), where each edge has a cost that is the same in both directions. Observe that the edge costs are not necessarily proportional to the coordinate based distance estimates.
The start node is S and the goal node is G, the MoveGen function returns neighbours in alphabetical order. Use Manhattan distance as the heuristic function.
Tie-breaker: when several nodes have the same best cost, use alphabetical order to break ties.

What is the cost of the path found by Branch-and-Bound algorithm?
Enter a natural number. NO SPACES, TABS, DOTS, BRACKETS OR EXTRANEOUS CHARACTERS. Answer format: 17

SEARCH
The figure shows a map with several locations on a grid where each tile is 1x1 in size. The locations are at grid points and are connected by two way edges (roads), where each edge has a cost that is the same in both directions. Observe that the edge costs are not necessarily proportional to the coordinate based distance estimates.
The start node is S and the goal node is G, the MoveGen function returns neighbours in alphabetical order. Use Manhattan distance as the heuristic function.
Tie-breaker: when several nodes have the same best cost, use alphabetical order to break ties.

SEARCH
The figure shows a map with several locations on a grid where each tile is 1x1 in size. The locations are at grid points and are connected by two way edges (roads), where each edge has a cost that is the same in both directions. Observe that the edge costs are not necessarily proportional to the coordinate based distance estimates.
The start node is S and the goal node is G, the MoveGen function returns neighbours in alphabetical order. Use Manhattan distance as the heuristic function.
Tie-breaker: when several nodes have the same best cost, use alphabetical order to break ties.

Is the heuristic admissible in the given map?

TSP
The distance matrix and sorted edge costs for 7 cities (A to G) are provided below. Note: sorted edge costs are derived from distance matrix.

TSP
The distance matrix and sorted edge costs for 7 cities (A to G) are provided below. Note: sorted edge costs are derived from distance matrix.
Solve the given subquestions using the TSP Branch-and-Bound algorithm.
Attention: Infer as much as possible (and as early as possible) about the permanent edges in the partial solutions.

What is the lower bound on the cost of the tours (S0) as per the TSP BnB algorithm discussed in class?
Enter a real number, round it to one decimal place. NO SPACES, TABS, DOTS, BRACKETS OR EXTRANEOUS CHARACTERS. Answer format: 17.3

TSP
The distance matrix and sorted edge costs for 7 cities (A to G) are provided below. Note: sorted edge costs are derived from distance matrix.

TSP
The distance matrix and sorted edge costs for 7 cities (A to G) are provided below. Note: sorted edge costs are derived from distance matrix.
Solve the given subquestions using the TSP Branch-and-Bound algorithm.
Attention: Infer as much as possible (and as early as possible) about the permanent edges in the partial solutions.

Infer all the permanently included edges in the node (AF,CG,DE,DF) in the TSP BnB search tree. Enter the total number of permanently included edges in the text box.
Enter a natural number. NO SPACES, TABS, DOTS, BRACKETS OR EXTRANEOUS CHARACTERS. Answer format: 42

TSP
The distance matrix and sorted edge costs for 7 cities (A to G) are provided below. Note: sorted edge costs are derived from distance matrix.

TSP
The distance matrix and sorted edge costs for 7 cities (A to G) are provided below. Note: sorted edge costs are derived from distance matrix.
Solve the given subquestions using the TSP Branch-and-Bound algorithm.
Attention: Infer as much as possible (and as early as possible) about the permanent edges in the partial solutions.

Infer all the permanently excluded edges in the node (AF,CG,DE,DF) in the TSP BnB search tree. Enter the total number of permanently excluded edges in the text box.
Enter a natural number. NO SPACES, TABS, DOTS, BRACKETS OR EXTRANEOUS CHARACTERS. Answer format: 42

TSP
The distance matrix and sorted edge costs for 7 cities (A to G) are provided below. Note: sorted edge costs are derived from distance matrix.

TSP
The distance matrix and sorted edge costs for 7 cities (A to G) are provided below. Note: sorted edge costs are derived from distance matrix.
Solve the given subquestions using the TSP Branch-and-Bound algorithm.
Attention: Infer as much as possible (and as early as possible) about the permanent edges in the partial solutions.

How many tours are represented by the node (AF,CG,DE,DF) in the TSP BnB search tree?
Enter a natural number NO SPACES, TABS, DOTS, BRACKETS OR EXTRANEOUS CHARACTERS. Answer format: 17

TSP
The distance matrix and sorted edge costs for 7 cities (A to G) are provided below. Note: sorted edge costs are derived from distance matrix.

TSP
The distance matrix and sorted edge costs for 7 cities (A to G) are provided below. Note: sorted edge costs are derived from distance matrix.
Solve the given subquestions using the TSP Branch-and-Bound algorithm.
Attention: Infer as much as possible (and as early as possible) about the permanent edges in the partial solutions.

What is the estimated cost of the node (AF,CG,DE,DF) in the TSP BnB search tree?
Enter a natural number. NO SPACES, TABS, DOTS, BRACKETS OR EXTRANEOUS CHARACTERS. Answer format: 17

GAMES
The figure shows a game tree with evaluations W (win), L (loss) and D (draw) from Max's perspective. The nodes are labeled in a level-by-level (a,b,...,e) left-to-right (1,2,...) manner as indicated in the game tree.

GAMES
The figure shows a game tree with evaluations W (win), L (loss) and D (draw) from Max's perspective. The nodes are labeled in a level-by-level (a,b,...,e) left-to-right (1,2,...) manner as indicated in the game tree.
Based on the above data, answer the given subquestions.

What is the outcome (W, D or L) of the game when both players play perfectly?
NO SPACES, TABS, DOTS, BRACKETS OR EXTRANEOUS CHARACTERS. Answer format: X

GAMES
The figure shows a game tree with evaluations W (win), L (loss) and D (draw) from Max's perspective. The nodes are labeled in a level-by-level (a,b,...,e) left-to-right (1,2,...) manner as indicated in the game tree.

GAMES
The figure shows a game tree with evaluations W (win), L (loss) and D (draw) from Max's perspective. The nodes are labeled in a level-by-level (a,b,...,e) left-to-right (1,2,...) manner as indicated in the game tree.
Based on the above data, answer the given subquestions.

Evaluation order matters. Evaluate the game tree in depth-first-search order (depth-first left-to-right order), for this evaluation order identify the “don’t care” nodes in level c, nodes c1 to c15. Enter one of the “don’t care” nodes and its value as a comma separated list.
NO SPACES, TABS, DOTS, BRACKETS OR EXTRANEOUS CHARACTERS. Answer format: a1,X

Based on the above data, answer the given subquestions.

List the horizon nodes in the best strategy.
Enter the node labels as a comma separated list in ASCENDING order. NO SPACES, TABS, DOTS, BRACKETS OR EXTRANEOUS CHARACTERS. Answer format: X,Y,Z

Based on the above data, answer the given subquestions.

List the horizon nodes pruned by Alpha-Beta algorithm.
Enter the node labels as a comma separated list in ASCENDING order. NO SPACES, TABS, DOTS, BRACKETS OR EXTRANEOUS CHARACTERS. Answer format: X,Y,Z

Based on the above data, answer the given subquestions.

List the horizon nodes in the initial cluster formed by SSS* algorithm.
Enter the node labels as a comma separated list in ASCENDING order. NO SPACES, TABS, DOTS, BRACKETS OR EXTRANEOUS CHARACTERS. Answer format: X,Y,Z

Based on the above data, answer the given subquestions.

List the horizon nodes assigned SOLVED status by the SSS* algorithm.
Enter the node labels as a comma separated list in ASCENDING order. NO SPACES, TABS, DOTS, BRACKETS OR EXTRANEOUS CHARACTERS. Answer format: X,Y,Z

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.
Tie-breaker for subgoal ordering: treat the start state, goal description, preconditions and effects as lists that are accessed from left to right. When the elements in a list are pushed one by one into a stack, the last element will be at the top of the stack. It has the effect of reversing the list.
Tie-breaker for block placement: when there are multiple locations for placing a block, choose the location that satisfies a goal at hand, or else, choose a location that will lead to a plan, or else, place it on the table.
Tie-breaker for action selection: when actions are chosen non-deterministically, choose actions that lead to a plan, even a suboptimal plan is fine. Throwaway the actions that may lead to loops.
A planning problem is given below, find a plan using the operators and predicates defined in the blocks-world domain.

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.
Tie-breaker for subgoal ordering: treat the start state, goal description, preconditions and effects as lists that are accessed from left to right. When the elements in a list are pushed one by one into a stack, the last element will be at the top of the stack. It has the effect of reversing the list.
Tie-breaker for block placement: when there are multiple locations for placing a block, choose the location that satisfies a goal at hand, or else, choose a location that will lead to a plan, or else, place it on the table.
Tie-breaker for action selection: when actions are chosen non-deterministically, choose actions that lead to a plan, even a suboptimal plan is fine. Throwaway the actions that may lead to loops.
A planning problem is given below, find a plan using the operators and predicates defined in the blocks-world domain.
Based on the above data, answer the given subquestions.

What is the length of the optimal plan? Enter the number of actions in the optimal plan.
NO SPACES, TABS, DOTS, BRACKETS OR EXTRANEOUS CHARACTERS. Answer format: 42

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.
Tie-breaker for subgoal ordering: treat the start state, goal description, preconditions and effects as lists that are accessed from left to right. When the elements in a list are pushed one by one into a stack, the last element will be at the top of the stack. It has the effect of reversing the list.
Tie-breaker for block placement: when there are multiple locations for placing a block, choose the location that satisfies a goal at hand, or else, choose a location that will lead to a plan, or else, place it on the table.
Tie-breaker for action selection: when actions are chosen non-deterministically, choose actions that lead to a plan, even a suboptimal plan is fine. Throwaway the actions that may lead to loops.
A planning problem is given below, find a plan using the operators and predicates defined in the blocks-world domain.

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.
Tie-breaker for subgoal ordering: treat the start state, goal description, preconditions and effects as lists that are accessed from left to right. When the elements in a list are pushed one by one into a stack, the last element will be at the top of the stack. It has the effect of reversing the list.
Tie-breaker for block placement: when there are multiple locations for placing a block, choose the location that satisfies a goal at hand, or else, choose a location that will lead to a plan, or else, place it on the table.
Tie-breaker for action selection: when actions are chosen non-deterministically, choose actions that lead to a plan, even a suboptimal plan is fine. Throwaway the actions that may lead to loops.
A planning problem is given below, find a plan using the operators and predicates defined in the blocks-world domain.
Based on the above data, answer the given subquestions.

Which of the following are applicable actions in the start state for the given planning problem?

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.
Tie-breaker for subgoal ordering: treat the start state, goal description, preconditions and effects as lists that are accessed from left to right. When the elements in a list are pushed one by one into a stack, the last element will be at the top of the stack. It has the effect of reversing the list.
Tie-breaker for block placement: when there are multiple locations for placing a block, choose the location that satisfies a goal at hand, or else, choose a location that will lead to a plan, or else, place it on the table.
Tie-breaker for action selection: when actions are chosen non-deterministically, choose actions that lead to a plan, even a suboptimal plan is fine. Throwaway the actions that may lead to loops.
A planning problem is given below, find a plan using the operators and predicates defined in the blocks-world domain.

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.
Tie-breaker for subgoal ordering: treat the start state, goal description, preconditions and effects as lists that are accessed from left to right. When the elements in a list are pushed one by one into a stack, the last element will be at the top of the stack. It has the effect of reversing the list.
Tie-breaker for block placement: when there are multiple locations for placing a block, choose the location that satisfies a goal at hand, or else, choose a location that will lead to a plan, or else, place it on the table.
Tie-breaker for action selection: when actions are chosen non-deterministically, choose actions that lead to a plan, even a suboptimal plan is fine. Throwaway the actions that may lead to loops.
A planning problem is given below, find a plan using the operators and predicates defined in the blocks-world domain.
Based on the above data, answer the given subquestions.

Which of the following are relevant actions for the goal description in the given planning problem?

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.
Tie-breaker for subgoal ordering: treat the start state, goal description, preconditions and effects as lists that are accessed from left to right. When the elements in a list are pushed one by one into a stack, the last element will be at the top of the stack. It has the effect of reversing the list.
Tie-breaker for block placement: when there are multiple locations for placing a block, choose the location that satisfies a goal at hand, or else, choose a location that will lead to a plan, or else, place it on the table.
Tie-breaker for action selection: when actions are chosen non-deterministically, choose actions that lead to a plan, even a suboptimal plan is fine. Throwaway the actions that may lead to loops.
A planning problem is given below, find a plan using the operators and predicates defined in the blocks-world domain.

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.
Tie-breaker for subgoal ordering: treat the start state, goal description, preconditions and effects as lists that are accessed from left to right. When the elements in a list are pushed one by one into a stack, the last element will be at the top of the stack. It has the effect of reversing the list.
Tie-breaker for block placement: when there are multiple locations for placing a block, choose the location that satisfies a goal at hand, or else, choose a location that will lead to a plan, or else, place it on the table.
Tie-breaker for action selection: when actions are chosen non-deterministically, choose actions that lead to a plan, even a suboptimal plan is fine. Throwaway the actions that may lead to loops.
A planning problem is given below, find a plan using the operators and predicates defined in the blocks-world domain.
Based on the above data, answer the given subquestions.

For the subgoal ordering given in the goal description (and using the given tie breaking rules) which of the following can be pushed as the first three elements onto the stack by the Goal Stack Planning algorithm? In the representation below, the bottom of the stack is on the right end, marked by END.

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.
Tie-breaker for subgoal ordering: treat the start state, goal description, preconditions and effects as lists that are accessed from left to right. When the elements in a list are pushed one by one into a stack, the last element will be at the top of the stack. It has the effect of reversing the list.
Tie-breaker for block placement: when there are multiple locations for placing a block, choose the location that satisfies a goal at hand, or else, choose a location that will lead to a plan, or else, place it on the table.
Tie-breaker for action selection: when actions are chosen non-deterministically, choose actions that lead to a plan, even a suboptimal plan is fine. Throwaway the actions that may lead to loops.
A planning problem is given below, find a plan using the operators and predicates defined in the blocks-world domain.

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.
Tie-breaker for subgoal ordering: treat the start state, goal description, preconditions and effects as lists that are accessed from left to right. When the elements in a list are pushed one by one into a stack, the last element will be at the top of the stack. It has the effect of reversing the list.
Tie-breaker for block placement: when there are multiple locations for placing a block, choose the location that satisfies a goal at hand, or else, choose a location that will lead to a plan, or else, place it on the table.
Tie-breaker for action selection: when actions are chosen non-deterministically, choose actions that lead to a plan, even a suboptimal plan is fine. Throwaway the actions that may lead to loops.
A planning problem is given below, find a plan using the operators and predicates defined in the blocks-world domain.
Based on the above data, answer the given subquestions.

For the subgoal ordering given in the goal description (and using the given tie breaking rules), which of the following is the first action popped out of the stack in Goal Stack Planning?

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.
Tie-breaker for subgoal ordering: treat the start state, goal description, preconditions and effects as lists that are accessed from left to right. When the elements in a list are pushed one by one into a stack, the last element will be at the top of the stack. It has the effect of reversing the list.
Tie-breaker for block placement: when there are multiple locations for placing a block, choose the location that satisfies a goal at hand, or else, choose a location that will lead to a plan, or else, place it on the table.
Tie-breaker for action selection: when actions are chosen non-deterministically, choose actions that lead to a plan, even a suboptimal plan is fine. Throwaway the actions that may lead to loops.
A planning problem is given below, find a plan using the operators and predicates defined in the blocks-world domain.

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.
Tie-breaker for subgoal ordering: treat the start state, goal description, preconditions and effects as lists that are accessed from left to right. When the elements in a list are pushed one by one into a stack, the last element will be at the top of the stack. It has the effect of reversing the list.
Tie-breaker for block placement: when there are multiple locations for placing a block, choose the location that satisfies a goal at hand, or else, choose a location that will lead to a plan, or else, place it on the table.
Tie-breaker for action selection: when actions are chosen non-deterministically, choose actions that lead to a plan, even a suboptimal plan is fine. Throwaway the actions that may lead to loops.
A planning problem is given below, find a plan using the operators and predicates defined in the blocks-world domain.
Based on the above data, answer the given subquestions.

For the subgoal ordering given in the goal description (and using the given tie breaking rules), does the Goal Stack Planning algorithm find an optimal plan?

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.
Tie-breaker for subgoal ordering: treat the start state, goal description, preconditions and effects as lists that are accessed from left to right. When the elements in a list are pushed one by one into a stack, the last element will be at the top of the stack. It has the effect of reversing the list.
Tie-breaker for block placement: when there are multiple locations for placing a block, choose the location that satisfies a goal at hand, or else, choose a location that will lead to a plan, or else, place it on the table.
Tie-breaker for action selection: when actions are chosen non-deterministically, choose actions that lead to a plan, even a suboptimal plan is fine. Throwaway the actions that may lead to loops.
A planning problem is given below, find a plan using the operators and predicates defined in the blocks-world domain.

AUTOMATED PLANNING
The domain description of a blocks-world with a single one-armed robot is provided below. Note: this is the same domain description used in the weekly assignments.
Tie-breaker for subgoal ordering: treat the start state, goal description, preconditions and effects as lists that are accessed from left to right. When the elements in a list are pushed one by one into a stack, the last element will be at the top of the stack. It has the effect of reversing the list.
Tie-breaker for block placement: when there are multiple locations for placing a block, choose the location that satisfies a goal at hand, or else, choose a location that will lead to a plan, or else, place it on the table.
Tie-breaker for action selection: when actions are chosen non-deterministically, choose actions that lead to a plan, even a suboptimal plan is fine. Throwaway the actions that may lead to loops.
A planning problem is given below, find a plan using the operators and predicates defined in the blocks-world domain.
Based on the above data, answer the given subquestions.

If the subgoals in the goal description are swapped places then does the Goal Stack Planning algorithm find an optimal plan?