From 4fb97c58d2b50e7ae347d95efd05756bdfb71f5f Mon Sep 17 00:00:00 2001 From: NotXia <35894453+NotXia@users.noreply.github.com> Date: Wed, 6 Dec 2023 09:14:25 +0100 Subject: [PATCH] Fix typos --- .../module1/sections/_local_search.tex | 4 ++-- src/fundamentals-of-ai-and-kr/module1/sections/_search.tex | 2 +- .../module1/sections/_swarm_intelligence.tex | 6 +++--- 3 files changed, 6 insertions(+), 6 deletions(-) diff --git a/src/fundamentals-of-ai-and-kr/module1/sections/_local_search.tex b/src/fundamentals-of-ai-and-kr/module1/sections/_local_search.tex index 5ea2b5a..2b2f949 100644 --- a/src/fundamentals-of-ai-and-kr/module1/sections/_local_search.tex +++ b/src/fundamentals-of-ai-and-kr/module1/sections/_local_search.tex @@ -91,7 +91,7 @@ Can be seen as a search process over graphs: \end{subfigure} \end{figure} -Meta heuristics finds a balance between: +Meta heuristics aim to find a balance between: \begin{descriptionlist} \item[Intensification] \marginnote{Intensification} Look for moves near the neighborhood. @@ -292,4 +292,4 @@ Genetic operators are: population = offspring evaluate(population) \end{lstlisting} -\end{algorithm} \ No newline at end of file +\end{algorithm} diff --git a/src/fundamentals-of-ai-and-kr/module1/sections/_search.tex b/src/fundamentals-of-ai-and-kr/module1/sections/_search.tex index 2646150..6e686b2 100644 --- a/src/fundamentals-of-ai-and-kr/module1/sections/_search.tex +++ b/src/fundamentals-of-ai-and-kr/module1/sections/_search.tex @@ -335,7 +335,7 @@ The fringe is ordered according the estimated scores. \end{tabular} \end{center} - In generally, it is better to use heuristics with large values (i.e. heuristics that don't underestimate too much). + In general, it is better to use heuristics with large values (i.e. heuristics that don't underestimate too much). \begin{figure}[ht] \centering diff --git a/src/fundamentals-of-ai-and-kr/module1/sections/_swarm_intelligence.tex b/src/fundamentals-of-ai-and-kr/module1/sections/_swarm_intelligence.tex index e001421..a5cebc3 100644 --- a/src/fundamentals-of-ai-and-kr/module1/sections/_swarm_intelligence.tex +++ b/src/fundamentals-of-ai-and-kr/module1/sections/_swarm_intelligence.tex @@ -74,8 +74,8 @@ They also tend to prefer paths marked with the highest pheromone concentration. \item[Pheromone update] After each step, the pheromone trail is updated depending on an evaporation factor $\rho \in [0, 1]$: \[ \tau_{ij} = (1 - \rho) \tau_{ij} + \sum_{k=1}^{n_\text{ants}} \Delta \tau_{ij}^{(k)} \] - $\tau_{ij}^{(k)}$ of the $k$-th ant is defined as: - \[ \tau_{ij}^{(k)} = \begin{cases} + $\Delta \tau_{ij}^{(k)}$ of the $k$-th ant is defined as: + \[ \Delta \tau_{ij}^{(k)} = \begin{cases} \frac{1}{L_k} & \text{if ant } k \text{ used the arch } (i, j) \\ 0 & \text{otherwise} \end{cases} \] @@ -172,7 +172,7 @@ In a bird flock, the movement of the individuals tend to: \item Stay in the flock. \item Avoid collisions. \end{itemize} -However, a model based on the these rules does not have a common objective. +However, a model based on these rules does not have a common objective. PSO introduces as common objective the search of food. Each individual that finds food can: