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| - | ===== Lab: Agents ===== | ||
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| - | ==== Before the lab ==== | ||
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| - | * **Reading: | ||
| - | * AIMA: **Chapter 2 - Intelligent Agents**. Focus on agents and environments, | ||
| - | * **Technical preparation: | ||
| - | * Open today' | ||
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| - | ==== Q&A ==== | ||
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| - | - Consider a robotic vacuum cleaner. What belongs to the agent, what belongs to the environment, | ||
| - | - A vacuum agent moves left even though the right location is dirty. Does this prove that the agent is irrational? What information would you need before deciding? | ||
| - | - What changes when the vacuum can perceive only whether its current location is clean or dirty, but cannot perceive its location or the condition of other locations? | ||
| - | - Suppose the vacuum receives one point whenever it removes dirt. How might it exploit this performance measure, and how should the measure be redesigned? | ||
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| - | ==== Notebook ==== | ||
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| - | **Notebook: | ||
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| - | Work in groups of 2-4. Every group member must be able to explain the results. | ||
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| - | ==== Challenge ==== | ||
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| - | Work in groups of **2-4** to build an agent for the [[https:// | ||
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| - | Your robot needs to collect samples, diagnose them, gather the required molecules, and produce medicines. Begin with a working state machine: | ||
| - | < | ||
| - | Next, make your agent smarter. Which samples are worth taking? Can they be completed with the available molecules? When should the robot change its plan? Should it react to the competing robot? | ||
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| - | Use these decisions to identify whether your solution behaves like a reflex, model-based, | ||
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| - | Start the challenge during the lab and continue it as part of the **self-study regarding classes**. Selected groups may share their strategies at the next lab, and effective solutions may receive bonus points. | ||
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| - | ==== Learn more! ==== | ||
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| - | * FIXME | ||