Quiz
Ai 2.3
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Questions in this quiz (21)
1Intelligent System = [blank_start]State space graph[blank_end] + [blank_start]Search algorithm[blank_end]
- AState space graph
- BSearch algorithm
2The task of a search algorithm is to find a [blank_start]solution path[blank_end] in a [blank_start]state space graph[blank_end].
- Asolution path
- Bstate space graph
3Solution path is a [blank_start]sequence of steps[blank_end] that leads from a [blank_start]search start node[blank_end] to a [blank_start]search goal node[blank_end].
- Asequence of steps
- Bsearch start node
- Csearch goal node
4Search start node: Specific node [blank_start]from which the search process starts[blank_end].
Search goal node: Specific node which [blank_start]shoud be reached in the search process[blank_end].
Root node: Node without [blank_start]ancestors[blank_end].
Leaf node: Node without [blank_start]decendents[blank_end].- Afrom which the search process starts
- Bwhere the search process ends
- Cshoud be reached in the search process
- Dshould be the start of the search proces
- Eancestors
- Fdecendents
5Def. Solution path
- ASequence of steps that leads from search start node to search goal node.
- BIs always a full path.
- CIs sometimes a full path.
- DIs any path from root node to leaf node.
- EIs any part of a full path.
- FThere can't be more than one in a SSG.
- GThere is always one in a SSG.
6Def. Full path
- AIs any path from a root node to a leaf node.
- BIs a path from search start node to search goal node.
- CIs a part of a solution path.
7Input for the search algorithm:
- ASearch start node
- BSearch goal node
- CRoot node
- DLeaf node
- EState space graph
- FSolution path
- GPartial path
8Def. Partial path
- AIs any part of a full path.
- BIs any path from root node to leaf node.
9Deployment means to [blank_start]generate[blank_end] the [blank_start]descendants[blank_end] or [blank_start]ancestors[blank_end] of a current node.
- Agenerate
- Bdescendants
- Cancestors
10Open nodes: Descendants or ancestors [blank_start]haven't been determined yet[blank_end].
Closed nodes: Descendants or ancestors [blank_start]have been already determined[blank_end].- Ahaven't been determined yet
- Bhave been already determined
11[blank_start]Open node[blank_end] --> Deployment --> [blank_start]Closed node[blank_end]
- AOpen node
- BClosed node
12Two ways to describe a goal state:
1) [blank_start]measurable[blank_end] property of the [blank_start]state[blank_end]
2) property of the [blank_start]solution path[blank_end]- Ameasurable
- Bstate
- Csolution path
13Availability of a SSG:
Is available: [blank_start]With knowledge about the SSG[blank_end]
Isn't available: [blank_start]Without knowledge about the hole SSG[blank_end]- AWith knowledge about the SSG
- BWithout knowledge about the hole SSG
14Which questions does the backtracking algorithm answer?
- AHow is the next node chosen from descendants of the current node? This influences how quickly the goal node will be found?
- BWhat should be done with nodes which have been discovered once walking along a path in the state space, and now appear again, changing the path?
- CWhat should be done with cycles, if they exist in the state space graph?
15Backtracking implementation: contains the states in the current path being tried ; if the search goal node is found, the list contains the ordered list of states on the solution path
- ASL (State List)
- BNSL (New State List)
- CDE (Dead Ends)
- DCS (Current State)
16Backtracking implementation: contains nodes awaiting evaluation (deployment)
- ASL ( State List)
- BNSL (New State List)
- CDE (Dead Ends)
- DCS (Current States)
17Backtracking implementation: contains states whose descendants have failed to contain the search goal node . If these states are encountered again, they will be detected as elements of this list and eliminated from consideration immediately
- ASL (State List)
- BNSL (New State List)
- CDE (Dead Ends)
- DCS (Current State)
18Backtracking implementation: a variable contains the current node (under consideration)
- ASL (State List)
- BNSL (New State List)
- CDE (Dead Ends)
- DCS (Current State)
19Uninformed search algorithms
- ADepth-First Search
- BBreadth-First Search
- CDepth-Limited Search
- DBidirectional Search
- EHill Climbing
- FBest-First Search
- GBeam Search
20Heuristically informed search algorithms
- ADepth-First Search
- BBreadth-First Search
- CDepth-Limited Search
- DBidirectional Search
- EHill Climbing
- FBest-First Search
- GBeam Search
21Characteristics of search algorithms:
Uninformed search: [blank_start]no informations[blank_end] about the quality of the states, search efficiency depends only on [blank_start]the structure of SSG[blank_end]
Heuristically informed search: [blank_start]information[blank_end] about the quality of the states- Ano informations
- Binformation
- Cthe structure of SSG
Information
- Description
- Quiz on Ai 2.3, created by Stella Mahler on 16/10/2017.
- Author
- Stella Mahler
- Language
- Deutsch
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