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8 votes

How to turn a ternary constraint into three binary constraints?

Let $D_a$ be the domain for A, and $a_i$ the elements of $D_a$. Let $D_b$ and $D_c$ work similarly for $B$ and $C$ respectively. We introduce $D_t = \{t | t = (c_i - b_j, c_i)\}$ for all $c_i$ in $...
jspencer's user avatar
  • 196
5 votes

What AI technique should I use to assign a person to a task?

What you have could be well described as a Task Allocation problem, which is studied as part of the planning subfield of AI. Chapters 10 & 11 of Russell & Norvig provide a good overview of ...
John Doucette's user avatar
3 votes

What are the differences between constraint satisfaction problems and linear programming?

LP is a mathematical problem to optimize a linear function subject to linear (in)equality constraints of the sort: $$ min_x w^t x $$ $$ Ax<b $$ where $x$ is a continuous variable (vector). If the ...
nikos's user avatar
  • 201
2 votes

How can I develop a genetic algorithm with a constraint on the sum of alleles?

There are multiple ways to handle 'illegal' individuals, each one with pros and cons: Abortive methods: The individuals that violate constraints are eliminated as soon as discovered (i.e. after ...
Alvin Sartor's user avatar
2 votes

How can I formulate the k-knights problem as a constraint satisfaction problem?

There are many possible ways to encode this problem, and some will be more advantageous than others An encoding that seems like a reasonable starting point to me is: Variables: Let $S$ be a set of $...
John Doucette's user avatar
2 votes

Which algorithm can I use to solve a problem with multiple objectives and constraints?

From your description, the problem you want to solve is a linear optimization problem: suppose we use the indices $i$ and $j$ to denote the $i-$th class and the $j-$th grade. Also, let us call $y_j$ ...
Diego Gomez's user avatar
2 votes

What is the goal of a constraint solver?

You want Chapter 6 of Russell & Norvig's AI: A Modern Approach, for a starting place. The goal of a constraint solver is to find an assignment of values to variables such that every variable is ...
John Doucette's user avatar
1 vote

How to handle equality constraints in the mutation operation of evolutionary algorithms?

If X is your 6D vector and m(X) is the mutated version of X, then you can renormalise the mutant back to unity by dividing by the sum of X, i.e. X' = m(X)/sum(X). However, I encourage you figure out ...
Mike NZ's user avatar
  • 401
1 vote

What's wrong with my answer to this constraint satisfaction problem, which needs to be solved the AC-3 algorithm?

To satisfy $D\ne A$, for each element in the domain of $D$, say $d$, there must be at least one element in the domain of $A$, say $a$, that $d \ne a$. Domain of $D$: $ \{ 1, 2, 3, 4 \} $ Domain of $A$:...
user153245's user avatar
1 vote

Have evolutionary algorithms been used for engineering design?

Examples of GA implementations: NASA’s spacecraft evolved antenna Solution for TSP with a big number of connections. Here is an example with Python and here with C#. From my experience, GA can be ...
Stepan Novikov's user avatar
1 vote

What are daily life examples of SAT problems?

SAT problems are decision problems that can be categorised as NPC. This informally means although there has not been any solution that can solve these problem in the polynomial order, the solutions of ...
Green Falcon's user avatar
1 vote

What is a successor function (in CSPs)?

A successor function is a function that generates a next state from the current state, plus the choices that affect state changes. In e.g. the 8 queens problem, a state might be the location of 5 ...
Neil Slater's user avatar
  • 32.4k

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