I will investigate methods currently used in computer graphics and also look at behaviour-based systems that are being used to build autonomous mobile robots. The robots deal in real-world environments rather than simulations so useful tasks may be carried out in an environment which has not been specially structured or engineered for it.
In this way I hope to develop creatures that do not have fixed responses to situations but react appropriately in a natural way based on how they perceive each situation.
A working simulation of the 'flock' and 'predator' in action is created in order to discover whether the predator can successfully herd the flock into a desired pen.
I hope to simulate completely autonomous agents that are seen as intelligent beings in their own right. I will call such agents TADPOIDS, for the purposes of the project. A collection of tadpoids forms a flock.
I will call the agent herding the tadpoids the PREDATOR.
There are some requirements for each element of the flock, a tadpoid, which must be considered.
- A tadpoid must cope appropriately and in a timely fashion with changes in its dynamic environment.
- A tadpoid should be able to maintain multiple goals and, depending on the circumstances it finds itself in, change which goals it is actively pursuing; thus it can both adapt to changing situations and react with urgency if required to do so.
- the behaviour of a tadpoid should be self-determined
I hope that through the development of realistic behaviours, including fleeing from the predator, the tadpoids may be herded into the pen.
As the emergent flock emanates from randomly generated motion, it is by essence unpredictable in its movement. Therefore, the problem of trying to coerce them into a specific area is not trivial. For this reason I see it as a suitably challenging Artificial Intelligence (AI) problem.
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