• Summary
  • Contents
  • Subject index

This unique, self-contained and accessible textbook provides an introduction to computational modelling neuroscience accessible to readers with little or no background in computing or mathematics. Organized into thematic sections, the book spans from modelling integrate and firing neurons to playing the game Rock, Paper, Scissors in ACT-R. This non-technical guide shows how basic knowledge and modern computers can be combined for interesting simulations, progressing from early exercises utilizing spreadsheets, to simple programs in Python.

Key Features include: Interleaved chapters that show how traditional computing constructs are simply disguised versions of the spreadsheet methods; Mathematical facts and notation needed to understand the modelling methods are presented at their most basic and are interleaved with biographical and historical notes for context; Numerous worked examples to demonstrate the themes and procedures of cognitive modelling.

An excellent text for upper-level undergraduate and postgraduate students taking courses in research methods, computational neuroscience / computational modelling, and cognitive science / neuroscience. It will be especially valuable to psychology students.

Agent-Based Modelling
Agent-based modelling
Objectives

After reading this chapter you should be able to:

  • understand what is meant by agent-based modelling;
  • enumerate the components of an agent-based model; and
  • implement an agent-based model using the NetLogo software.
22.1 Overview

A relatively new use of computational modelling in neuroscience and psychology has been the elaboration of an agent-based approach. The growth of this method directly parallels the growth of affordable, desktop ...

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