Abstract
The emergence of behavioural and structural congruence based on simple local interactions of atomic units is a fascination to the scientific community across many disciplines. The climax of behavioural congruence and emergence of behaviour is exemplified by the community life-style of ants. Each individual ant possesses the capability only to solve part of the overall puzzle while aggressively communicating in primitive methods with the spatially related neighbours to produce emergent behaviour. The primary hypothesis of this research is that the constituent atomic actions of a complex behaviour could be successfully coordinated by a collection of collaborative and autonomous agents with the use of Action Templates. The AAANTS (Adaptive Autonomous Agent colony interactions with Network Transparent Services) model was conceptualised and implemented as a platform to represent the biologically inspired coordination and learning model to test the research hypothesis. The domain of foraging in a grid-world was identified as the experimental basis to evaluate the AAANTS coordination model. The experiments demonstrated relative improvements in achieving behavioural congruence using the AAANTS model in relation to the traditional Monte-Carlo based methods.Keywords: Collective Intelligence, Action Templates, Emergent Behaviour, Reinforcement Learning, Frame Representation.doi: 10.4038/icter.v1i1.449The International Journal on Advances in ICT for Emerging Regions 2008 01 (01) : 24 - 32
Highlights
The survival of an entity in the environment is directly attributed to selecting the most appropriate and refined behaviour with respect to the rapid changes in the environment
The primary hypothesis of this research is that the constituent atomic actions of a complex behaviour could be successfully coordinated by a collection of collaborative and autonomous agents with the use of Action Templates
The adaptive entities in the natural world use emergent models to achieve behavioural congruence. These models begin with an innate layer of basic incongruent atomic behaviour, which based on the reinforcements and or supervisions from the environment reaches a level of refinement more aligned with the demands of the environment
Summary
The survival of an entity in the environment is directly attributed to selecting the most appropriate and refined behaviour with respect to the rapid changes in the environment. The adaptive entities in the natural world use emergent models to achieve behavioural congruence. These models begin with an innate layer of basic incongruent atomic behaviour, which based on the reinforcements and or supervisions from the environment reaches a level of refinement more aligned with the demands of the environment. The simulations and experiments discussed in this paper were based on the domain of grid-world navigation This model could be applied to the domains of pattern recognition, robotic movement and vision navigation. The subsequent sections of the paper discuss the conceptualisation, realisation and experimentation of the AAANTS model within the domain of foraging in a grid-world. The conclusion of the research with respect to the defined objectives of the research is discussed in the last section
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