This is a large scale simulation model under development at the Theoretical Ecology Group, University of Bergen, 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 behaviour. From this we will research into adaptive goal-directed behaviour that is guided by the external environment and still is endogeneously generated.
We think of the AHA Model as a simple yet powerful general cognitive architecture that could be used for many research topics crossing traditional boundaries between animal behaviour, ecology, evolution, artificial intelligence and high performance computing. It has close connection with complex systems, affective computing and evolutionary robotics.
We think that understanding and modelling complex adaptive behaviour requires both extraneous (environmental) factors and stimuli as well as endogeneous architectural mechanisms that produce the behaviour. Explicit proximate representation of the motivation and emotion systems, self-prediction can be an important component linking environment, genes, physiology, behaviour, personality and elementary consciousness. Other research topics include consequences of emotion and personality to population ecology.
Even though the framework is general enough and could potentially account for simple forms of our own species, we use a simple model system based on fish physiology and behaviour that dwell in a simple 3D environment. However, by the general and abstract nature of the model, it is not based on any concrete fish species.
The AHA Model is implemented in the Fortran language (F2003-F2008 standards). It has the following main features:
AHA Model code comprises a framework for developing various implementations of complex evolutionary agent-based models.
AHA Model code is object oriented and massively modular. Modern Fortran supports most features of object oriented programming.
AHA Model code follows the "Literate programming" philosophy by integrating both the computer code and human readable documentation. The human documentation is actually the main part of the code.
AHA Model code uses only portable language constructions. Therefore, it can be built using different Fortran compilers and can run on various platforms and operating systems.
AHA Model code is intended to run in a HPC environment and therefore has (currently) no graphical user interface.
The source code of the AHA Model integrates detailed documentation on all major implementation aspects.
The source code of the model can be obtained here.
The software and tools that are required for working with the AHA Model are described in the AHA Modelling Tools Manual. This manual can also be downloaded as a PDF document.
The project "Adaptive Heuristics and Architecture" (AHA!) is supported by the Research Council of Norway, grant FRIMEDBIO 239834. AHA! is also a partner project of Centre for Digital Life Norway.