new

[book_gpu.git] / BookGPU / Chapters / chapter17 / ch17.tex

diff --git a/BookGPU/Chapters/chapter17/ch17.tex b/BookGPU/Chapters/chapter17/ch17.tex
index 6ad3a8c663019c9d14f1caf79642264ae2d7c1c7..28e8251421d8a72c9cc4f13a965cafa148224348 100755 (executable)
--- a/BookGPU/Chapters/chapter17/ch17.tex
+++ b/BookGPU/Chapters/chapter17/ch17.tex
@@ -11,7 +11,7 @@
   \setlength\hangindent{\mylen}%
   \hspace*{\mylen}#1\\}
 
-\chapter{Implementing MAS on GPU}
+\chapter{Implementing Multi-Agent Systems on GPU}
 \label{chapter17}
 
 
@@ -47,7 +47,7 @@ solution to increase simulation performance but Graphical Processing
 Units (GPU) are also a promising technology with an attractive
 performance/cost ratio.
 
-Conceptually a MAS is a distributed system as it favors the definition
+Conceptually a MAS\index{Multi-Agent System} is a distributed system as it favors the definition
 and description of large sets of individuals, the agents, that can be
 run in parallel. As a large set of agents could have the same behavior
 a SIMD model should fit the simulation execution. Most of the
@@ -299,7 +299,7 @@ collembolas in fields and forests. It is based on a diffusion
 algorithm which illustrates the case of agents with a simple behavior
 and few synchronization problems.
 
-\subsection{The Collembola model}
+\subsection{The Collembola model\index{Collembola model}}
 \label{ch17:subsec:collembolamodel}
 
 The Collembola model is an example of multi-agent system using GIS (Geographical Information System)