public:t-622-arti-15-1:lab_1_-_agents
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| public:t-622-arti-15-1:lab_1_-_agents [2015/01/13 15:59] – created stephan | public:t-622-arti-15-1:lab_1_-_agents [2024/04/29 13:33] (current) – external edit 127.0.0.1 | ||
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| The robot is equipped with a dust sensor and a touch sensor. If there is dirt at current location of the robot, the agent will sense " | The robot is equipped with a dust sensor and a touch sensor. If there is dirt at current location of the robot, the agent will sense " | ||
| The goal is to clean all cells and return to the initial location before turning the robot off. Note, a full charge of the battery of the robot will only last for a limited number of actions. | The goal is to clean all cells and return to the initial location before turning the robot off. Note, a full charge of the battery of the robot will only last for a limited number of actions. | ||
| + | |||
| + | To make this a bit easier you can use the following assumptions: | ||
| + | * The room is rectangular (not necessarily quadratic). It has only 4 straight walls that meet at right angles. There are no obstacles in the room. That is, the strategy "Go until you bump into a wall then turn right and repeat" | ||
| + | * The room is fairly small, so that 100 actions are enough to visit every cell, suck all the dirt and return home given a halfway decent algorithm (at least for the small environments, | ||
| ===== Tasks ===== | ===== Tasks ===== | ||
| - | - Characterise the environment (is it static or dynamic, deterministic or stochastic, ...). | + | - Characterise the environment (is it static or dynamic, deterministic or stochastic, ...) according to all 6 properties mentioned on slide 13 (Agents) or section 2.3.2 in the book. |
| - Develop a strategy for the agent such that it cleans every cell and outline the agent function. | - Develop a strategy for the agent such that it cleans every cell and outline the agent function. | ||
| - | - Fill out the missing parts of the vacuum cleaner Java program (see below) such that it encodes your agent function. | + | - Implement |
| - Test your program with all three provided environments. Record the number of steps it takes to finish each environment and the resulting points. | - Test your program with all three provided environments. Record the number of steps it takes to finish each environment and the resulting points. | ||
| - Is your agent rational? Justify your answer. | - Is your agent rational? Justify your answer. | ||
| - | |||
| - | To make this a bit easier you can use the following assumptions: | ||
| - | * The room is rectangular. It has only 4 straight walls that meet at right angles. There are no obstacles in the room. That is, the strategy "Go until you bump into a wall then turn right and repeat" | ||
| - | * The room is fairly small, so that 100 actions are enough to visit every cell, suck all the dirt and return home given a halfway decent algorithm. | ||
| ===== Submit ===== | ===== Submit ===== | ||
| - | * Answers to questions 1, 2, 4 and 5 (as doc, txt or pdf) and your source code in a zip archive. | + | * Answers to questions 1, 2, 4 and 5 (as doc, txt or pdf) and your source code in a zip archive |
| ===== Material ===== | ===== Material ===== | ||
/var/www/cadia.ru.is/wiki/data/attic/public/t-622-arti-15-1/lab_1_-_agents.1421164761.txt.gz · Last modified: 2024/04/29 13:32 (external edit)