Abstract
Directions for Bio-Inspired Artificial Intelligence
Highlights
Bio-inspired Artificial Intelligence [1] attempts to synthetically produce systems that exhibit intelligence by taking inspiration from the processes of natural life systems
There is no design constraint in the field of Artificial Intelligence to restrict oneself to applying exactly the same mechanisms to those used by natural life systems, the “wrongness” of the particular model in reproducing natural intelligence can be a useful guide in measuring the success of a bio-inspired AI model
Many of the important advances in the field of Artificial Intelligence (AI) such as artificial neural networks and evolutionary algorithms have taken their inspiration from biology
Summary
Bio-inspired Artificial Intelligence [1] attempts to synthetically produce systems that exhibit intelligence by taking inspiration from the processes of natural life systems. It is often important to revisit the design objectives of the original research by drawing further inspiration from real-life systems This can be done by examining those phenomena which are not covered well by the model and exploring alternative solutions, or by trying to extend the model to improve the realism and analyse where the model is wrong. With this in mind, three research directions that are currently being explored by the author of this article are described below: firstly, the problem of concept representation and learning, with specific focus on colour recognition; secondly, improvements in existing evolutionary algorithms which take their inspiration from natural evolutionary processes; and thirdly, real-time behavioural animation of virtual creatures and virtual humans. The first area is an example of using the validation approach advocated in this article; the second area shows how significant improvements in performance can be made by making modifications inspired by biological mechanisms not included in the original model; and the third area in real-time animation uses agents that are embodied and situated in virtual environments that can be visually analysed to assess the realism of the models
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