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Questions and Answers
What is the primary difference between informed search and uninformed search algorithms?
What is the primary difference between informed search and uninformed search algorithms?
- Informed search is used for goal-based agents, while uninformed search is used for problem-solving agents.
- Informed search is faster, while uninformed search is more accurate.
- Informed search uses a transition model, while uninformed search does not.
- Informed search has additional information to judge the promise of an action, while uninformed search does not. (correct)
What is the search strategy defined by?
What is the search strategy defined by?
- The method used to traverse the search tree.
- The method used to formulate the search problem.
- The method used to evaluate the goal test.
- The method used to choose the next node from available actions. (correct)
What is the primary purpose of the transition model in a search problem formulation?
What is the primary purpose of the transition model in a search problem formulation?
- To determine the goal state.
- To define the available actions. (correct)
- To provide additional information for informed search.
- To evaluate the step/path cost.
What type of agent is most likely to use a search algorithm?
What type of agent is most likely to use a search algorithm?
What is the purpose of the goal test in a search problem formulation?
What is the purpose of the goal test in a search problem formulation?
What is the primary advantage of using an informed search algorithm over an uninformed search algorithm?
What is the primary advantage of using an informed search algorithm over an uninformed search algorithm?
What is the primary goal of a goal-based agent?
What is the primary goal of a goal-based agent?
What is the term for the process of looking for a sequence of actions to reach a goal?
What is the term for the process of looking for a sequence of actions to reach a goal?
What is the requirement for defining a search problem?
What is the requirement for defining a search problem?
What is the characteristic of a search problem environment?
What is the characteristic of a search problem environment?
What is the term for the function that describes the possible actions available at each state?
What is the term for the function that describes the possible actions available at each state?
What is the purpose of a transition model in a search problem?
What is the purpose of a transition model in a search problem?
What is an optimal solution in a search problem?
What is an optimal solution in a search problem?
What is the primary assumption of a goal-based agent?
What is the primary assumption of a goal-based agent?
What is the primary difference between a state space graph and a search tree?
What is the primary difference between a state space graph and a search tree?
What is the main advantage of constructing the search tree on demand?
What is the main advantage of constructing the search tree on demand?
In a search tree, what does each node represent?
In a search tree, what does each node represent?
What is the purpose of checking for repeated states in a search algorithm?
What is the purpose of checking for repeated states in a search algorithm?
What is the main difference between a general tree search and a goal-based search?
What is the main difference between a general tree search and a goal-based search?
What is the benefit of using a data structure to store the frontier nodes in a search algorithm?
What is the benefit of using a data structure to store the frontier nodes in a search algorithm?
What is the purpose of a search strategy in a goal-based search?
What is the purpose of a search strategy in a goal-based search?
What is the main advantage of using a search tree instead of a state space graph?
What is the main advantage of using a search tree instead of a state space graph?
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Study Notes
Search Algorithms
- Types of search algorithms: Uninformed Search and Informed Search
- Uninformed Search: only has information provided by problem formulation (initial state, available actions, transition model, goal test, and step/path cost)
- Informed Search: has additional information to judge promise of an action, i.e. estimated cost from a state to a goal
Agents
- Key differences between agents: capabilities, decision-making processes, handling of uncertainty, and adaptability to environments and tasks
- Simple reflex agents: most basic, goal-based agents: intermediate in complexity, and learning agents: adaptive and capable of improving performance through experience
Goal-Based Agent
- Also called a problem-solving agent or planning agent
- Performs actions to get from initial state to a goal
- Process of looking for a sequence of actions to reach a goal is called search
- Requirements of searching:
- Define problem
- Represent search space by states
- Define actions the agent can perform
- Define costs associated with actions
- Define a goal: what is the agent searching for?
- Define a solution: an action sequence that reaches a goal state
- An optimal solution has the least cost among all solutions
Search Problem Formulation
- A search problem consists of five components:
- Initial state (S0) that the agent starts in
- Possible actions available at each state (Successor Function)
- Transition model describing what each action does
- Goal test
- Path cost function
State Space Graphs and Search Trees
- State Space Graph: represents all possible states and transitions
- Search Tree: a partial representation of the state space graph, constructed on demand
- Main variations of tree search:
- Which leaf node to expand next
- Whether to check for repeated states
- Data structures for frontier, expanded nodes
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