The extended ramp model: A biomimetic model of behaviour arbitration for lightweight cognitive architectures

In this article, we present an idea for a more intuitive, low-cost, adjustable mechanism for behaviour control and management. One focus of current development in virtual agents, robotics and digital games is on increasingly complex and realistic systems that more accurately simulate intelligence found in nature. This development introduces a multitude of control parameters creating high computational costs. The resulting complexity limits the applicability of AI systems. One solution to this problem it to focus on smaller, more manageable, and flexible systems which can be simultaneously created, instantiated, and controlled. Here we introduce a biologically inspired systems-engineering approach for enriching behaviour arbitration with a low computational overhead. We focus on an easy way to control the maintenance, inhibition and alternation of high-level behaviours (goals) in cases where static priorities are undesirable. The models we consider here are biomimetic, based on neuro-cognitive research findings from dopaminic cells responsible for controlling goal switching and maintenance in the mammalian brain. The most promising model we find is applicable to selection problems with multiple conflicting goals. It utilizes a ramp function to control the execution and inhibition of behaviours more accurately than previous mechanisms, allowing an additional layer of control on existing behaviour prioritization systems.     

Instinct: A biologically inspired reactive planner for intelligent embedded systems

The Instinct Planner is a new biologically inspired reactive planner, based on an established behaviour based robotics methodology and its reactive planner component — the POSH planner implementation. It includes several significant enhancements that facilitate plan design and runtime debugging. It has been specifically designed for low power processors and has a tiny memory footprint. Written in C++, it runs efficiently on both Arduino (Atmel AVR) and Microsoft VC++ environments and has been deployed within a low cost maker robot to study AI Transparency. Plans may be authored using a variety of tools including a new visual design language, currently implemented using the Dia drawing package.