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The marking criteria assume there is a working code implementing the individual objectives: Evolutionary & Adaptive Computing Course Work, UOY, UK
| University | University of York (UOY) |
| Subject | Evolutionary & Adaptive Computing |
The marking criteria assume there is a working code implementing the individual objectives. Partial marks may be allocated for design alone. No results will be accepted if the corresponding parts of the code involved in their generation cannot be executed.
- Choose a simple and efficient representation of your agents’ behaviour that would also allow for adaptation. Describe the chosen representation in the NetLogo Info section and explain the reasons behind it.
- Provide the necessary, working code, describing how running the simulation is going to provide the basis for estimating the fitness of your agents’ adaptive behaviour, and show how training examples for the learning component of your algorithm will be generated if needed.
- Describe the design of, and implement a procedure that uses adaptation, and possibly learning, to produce a viable behaviour for your agents.
- Design and describe an evaluation procedure that allows you to compare the behaviour obtained through adaptation to a non-adaptive behaviour, and draw conclusions that are supported by results that are statistically significant, and based on the most appropriate statistical tests. Assume all agents are capable of changing their behaviours at the same time.
- Collect experimental evidence, carrying out and showing the results of the evaluation procedure described above.
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