public:t-720-atai:atai-21:final_project_2
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public:t-720-atai:atai-21:final_project_2 [2021/10/19 10:30] – [Description] thorisson | public:t-720-atai:atai-21:final_project_2 [2021/10/19 10:32] (current) – removed thorisson | ||
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- | ====ATAI-21 Reykjavik University==== | ||
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- | ======Final Project====== | ||
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- | ====Description==== | ||
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- | For the final project you are asked to implement **//your own original task//** into the TestChamber (see **[[/ | ||
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- | * [[/ | ||
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- | Your task must have:\\ | ||
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- | - A **causal chain** with a length of at least three (3) steps (e.g. three out of: get a key, open door, activate switch, bake pizza, eat pizza). | ||
- | - **At least TWO solutions** that are: | ||
- | - independent of each other, i.e. mutually exclusive | ||
- | - include some different objects that need to be handled by NARS | ||
- | - composed of least three (3) steps of causal chains | ||
- | - At least one **own object** that is included in the task (e.g. WireCutter to stop active wires): | ||
- | - For this you might have to include a new Action Operator for NARS | ||
- | - You might have to change parts of the existing code to include the new actions and objects | ||
- | - An **own set of predefined knowledge** which can be loaded in the GUI to realise NARS solving the task. (Add a new “knoMenu” to the EditorPanel.java file in the grid2d folder of the opennars-lab source code which includes knowledge of the new object and/ or additional information which can be useful for NARS) **You can use this set of predefined knowledge to teach NARS about the different causalities instead of forcing actions repeatedly** | ||
- | - A “training scenario” must be provided in which NARS learns about the single causal connection (e.g. Key-> | ||
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- | Write a report on your findings (max. 5 pages + appendix). For this you can choose to focus on one or both of the following: | ||
- | - Analyze the **abduction** of NARS to abduct causal chains from single causal connections. Some questions that you may want to answer with respect to that might include: | ||
- | - What role, if any, does abduction play in NARS’ behavior? | ||
- | - What are the abduction mechanisms that NARS is deploying? | ||
- | - Is there a limit to the abduction abilities of NARS (e.g. length of causal chain)? | ||
- | - Analyze the **induction** of NARS to generate new rules which result in the possibility to solve a novel task. Some questions that you may want to answer with respect to that might include: | ||
- | - What role, if any, does induction play in NARS’ behavior? | ||
- | - What might be the limits of NARS’ induction in this world? Is it limited in some way (by the reasoning methods of NARS or the task-environment)? | ||
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- | //EOF// | ||
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