Sources

AI sources:
  • CS188 Artificial Intelligence (UC Berkeley course)

Computer Architecture sources:
  • CS61C Machine Structures and Computer Architecture (UC Berkeley course)

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Tips on Pointers and Arrays in C

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*p++ vs. (*p)++   *p++ means *(p++) ++ binds to p , not to *p ++ will increment "p," not "*p," which is the thing that "p" points to The value of the expression *p++ is the value that p pointed to before being incremented ( *p ) Two useful charts Pointer arithmetic notes (~pointer~) += (~number~);  means  (~pointer~) += ~number~) * sizeof((~type~)); Pointer arithmetic addition adds multiples of the type size to the memory address Ex. If p is a pointer to an integer, then p += 1 means p += 1 * sizeof(int)   (~pointer name~) + 1 points to the next object in memory (returns a pointer to the next element)  (~pointer name~) + i points to the i -th object beyond (~pointer name~) in memory  (~pointer name~) += i increments (~pointer name~) to point to i elements beyond itself  Types of valid pointer arithmetic Adding an integer to a pointer Subtracting 2 pointers (in the same array) Comparing...
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Constraint Satisfaction Problems

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identification problem  - a problem in which the agent must identify whether it is a goal state or not, with no regards of how it arrives at that goal In identification problems, the goal itself it important, not the path of reaching the goal All paths have the same depth, which is the number of variables in the problem constraint satisfaction problem (CSP)  - an identification search problem in which each state must satisfy a number of constraints (limitations) in order to be a valid goal state In CSPs, states are partial assignments  of variables (i.e. some variables have been assigned values while others have not) constraint graph  - a graph whose nodes represent a CSP's variables and edges represent the constraints between the variables/nodes Components of a CSP variables - a set of $N$ variables ($X_1,...,X_N$) that can each take on a single value from the domain domain  - a set ${x_1,...,x_d}$ representing all possible values that a ...
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Standard/Planning Search Problems

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Standard search problems Solution to a standard search problem: a plan Use a search algorithm  to find the plan and solve the search problem Search algorithms are performed on the search tree (of the problem) to find the solution to the search problem All search algorithms follow the same algorithm, but just use a different data structures for the fringe   Types of standard searches ➤  UNINFORMED SEARCH uninformed search  - a search that does not know information about the goal's location Types of uninformed searches Depth first search (DFS) - a search strategy that expands the deepest node first Implementation : uses a last-in-first-out (LIFO)  stack as the fringe Time complexity : $O(b^m)$, for a finite tree where $m$ is the maximum depth and $b$ is the branching factor Space complexity : $O(bm)$ DFS expands only the nodes on a single path from the deepest level to the root Breadth first search (BFS) - a search strategy in ...
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