Introduction and Getting Started

The AHA Model

This is a large scale simulation model (under development) that implements
a general decision-making architecture in evolutionary agents. Each
agent is programmed as a whole virtual organism including the genome,
rudimentary physiology, the hormonal system, a cognitive architecture and
behavioural repertoire. They “live” in a stochastic spatially explicit
virtual environment with physical gradients, predators and prey. The primary
aim of the whole modelling machinery is to understand the evolution of
decision making mechanisms, personality, emotion and behavioural plasticity
within a realistic ecological framework. An object-oriented approach coupled
with a highly modular design not only allows to cope with increasing layers
of complexity inherent in such a model system but also provides a framework
for the system generalizability to a wide variety of systems. We also use
a “physical-machine-like” implementation philosophy and a coding standard
integrating the source code with parallel detailed documentation that
increases understandability, replicability and reusability of this model
system.

The cognitive architecture of the organism is based on a set of
motivational (emotional) systems that serves as a common currency for
decision making. Then, the decision making is based on predictive
assessment of external and internal stimuli as well as the agent’s own
motivational (emotional) state. The agent makes a subjective assessment
and selects, from the available repertoire, the behaviour that would reduce
the expected motivational (emotional) arousal. Thus, decision making is
based on predicting one’s own internal state. As such, the decision-making
architecture integrates motivation, emotion, and a very simplistic model
of consciousness.

The purpose of the AHA model is to investigate a general framework
for modelling proximate decision-making and behavior. From this we will
investigate adaptive goal-directed behaviour that is both guided by the
external environment and still is endogeneously generated.

Other research topics include individual differences, personality as well
as consequences of emotion and personality to population ecology.

We think that understanding and modelling complex adaptive behaviour requires
both extraneous (environmental) factors and stimuli as well as endogeneous
mechanisms that produce the behaviour. Explicit proximate representation
of the motivation and emotion systems, self-prediction can be an important
component in linking environment, genes, physiology, behavior, personality
and consciousness.

Fortran is used due to its simplicity and efficiency. For example, check out
this paper.

Subdirectories of the AHA Model code

\dox — contains pictures, plots and other resources for the full Doxygen
documentation that is extracted from the source code.
\pfunit — unit tests using pFUnit, so
far rather rudimentary.
\tools — various accessory tools, post-processing of the data generated
by the model etc.
.

Getting started

Building and running the mode is based on the GNU Make. Both the AHA Model
code and the HEDTOOLS (code or static library) are needed to build the
model. These two components of the AHA Model framework are described in the
Overview of the AHA Fortran modules.

Normally, the AHA Model code and the HEDTOOLS code are placed in two
subdirectories of the working directory using two separate commands to get the
code of the AHA Model and HEDTOOLS from the repositories (svn co https://...
or hg clone ssh://... if Mercurial is used — check out
Subversion).

With the current main Subversion repository, getting the code requires these
commands:

svn co https://subversion.uib.no/repos/aha-fortran/tags/AHA_R/R1 AHA-R1
svn co https://subversion.uib.no/repos/aha-fortran/tags/HEDTOOLS/1.1 HEDTOOLS

or these, if Mercurial is used (here local folders are capital):

hg clone https://bitbucket.org/teg_uib/aha-r1 AHA-R1
hg clone ssh://hg@bitbucket.org/teg_uib/hedtools HEDTOOLS

or still these, if GitHub git-based repo is used:

git clone git@github.com:sbudaev/AHA-R1.git
git clone git@github.com:sbudaev/HEDTOOLS.git

Thus, the layout of the working directory after HEDG2_01 and HEDTOOLS are
downloaded is like this:

workdir
 |
 |-- AHA-R1
 |    |-- dox
 |    |-- pfunit
 |    `-- tools
 |
 `-- HEDTOOLS

Building the AHA Model is done in the model directory (here HEDG2_01). If
you use the terminal, go there with

cd AHA-R1

Here are the main commands to build and run the AHA Model:

Build the model from the source code: make;
Build and run the model:make run;
Delete all build-related, data and temporary files make distclean;
Get a quick help from the make system: make help.

See Makefile for build
configuration. To get more information on the GNU Make see
AHA Modelling Tools Manual,
Using Microsoft Visual Studio and
Using Code::Blocks IDE.

Environment variables

The model makes use of several environment variables to control certain
global aspects of the execution. These variables have the AHA_ prefix
and are listed below.

AHA_DEBUG=TRUE sets the “debug mode”;
AHA_SCREEN=NO sets logger to write to the standard output as well
as in the log file;
AHA_DEBUG_PLOTS=YES enables generation of debug plots;
AHA_ZIP_FILES=YES enables background compression of big output data files;
AHA_CHECK_EXTERNALS=NO disables checking for external executable
modules (this is a workaround against Intel Fortran compiler bug).

Makefile: GNU Make build configuration

Makefile to build the model
executable from the source code.

This is a standard GNU Make
Makefile to build the model from
the sources. It also automatically generates some platform and
compiler specific include files for the BASE_RANDOM and the
IEEE math modules. See
Working with the model
section for details.

In addition to the GNU Make, this
Makefile also depends on the
grep, cut, sed and awk utilities that are installed on any
Unix/Linux system, but usually absent on Windows. For Windows
they can be obtained from several locations on the web, e.g.
Cygwin or GnuWin32. See
AHA Modelling Tools Manual
for more information.

Main adjustable parameters

FC sets the default compiler type. Normally GNU gfortran or Intel
ifort.
HOST_HPC_ROOT is the hostname to run the model executable in the
HPC batch mode. If the hostname the
Makefile is called in is this
system, make run starts a new batch task. Otherwise, the model
executable is just started normally.
SRC is the name of the main source code (can be several files).
DRV is the source code of the model “driver”, that is the main
Fortran program that produces the executable. It should be very
very small. The “driver” is a separate file from the AHA Model
modules.
OUT is the executable file name that is actually run, on the
Windows platform must have the .exe suffix. By default, the
executable name is set to MODEL.exe for maximum portability.
DOXYCFG the Doxygen documentation system configuration file name.
DOXYPATH defines the Doxygen output directory where the
documentation is generated. This could be set manually or parsed
automatically using the grep command. Note that the output
directory is set in the Doxyfile as:
OUTPUT_DIRECTORY = ./model_docs.
HEDTOOLS is the list of HEDTOOLS Fortran source files that are
used in the AHA Model. Note that BASE_STRINGS in the list must
go before BASE_CSV_IO because BASE_CSV_IO depends on
procedures from BASE_STRINGS.
HEDTOOLSDIR defines the path to the HEDTOOLS source code.
IEEEPATH defines the path to the IEEE non-intrinsic math modules
(part of HEDTOOLS).
WINRM defines the command that is used to delete files and
directories on the Windows platform. The native file delete command on
the Windows platform is del or erase. However, if Cygwin is used,
this native file removal command may not call with a “command not found”
error. In such a case, use the Unix rm tool provided by Cygwin.
.

The source code of the Makefile
contains many other parameters and is well documented throughout.