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--- public:t-720-atai:atai-20:final_project_2 [2020/10/10 12:28] – thorisson
+++ public:t-720-atai:atai-20:final_project_2 [2024/04/29 13:33] (current) – external edit 127.0.0.1
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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, implemented by your team. This task must have:\\
+For the final project you are asked to implement **//your own original task//** into the TestChamber (see [[/public:t-720-atai:atai-20:final_project|Introduction]] to the Final Project), implemented by you and your collborator.
+Your task must have:\\
 \\
-  - A **causal chain** with a length of at least 5 (E.g. Get the Key, open the door, activate the switch, bake some pizza, eat the pizza).
+  - A **causal chain** with a length of at least 3 (E.g. Get the Key, open the door, activate the switch, bake some pizza, eat the pizza) - If you already have done more than 3 or feel like you have enough time to do more you can do so, everything over 3 will give you bonus points.
   - **Multiple solutions** independent of each other:
     - at least two of them must be mutually exclusive
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     - 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)
+  - 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->Door and switch->oven and oven->pizza) **independently**, such that it can learn before trying to complete the full task by trying things - or being shown - in the training room.
-Write a report on your findings. For this you can choose to focus on one or both of the following:
+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’ behaviour?
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     - 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’s behavior?
+    - What role, if any, does induction play in NARS’ behavior?
-    - What might be the limits of NARS’s induction in this world? Is it limited in some way (by the reasoning methods of NARS or the task-environment)?
+    - 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)?