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Learn about the vacuum cleaner problem, a classic search problem for an agent in AI. Find out the states, actions, goals and performance measures of this problem and how to solve it using best-first search.
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Developed a simple problem solving reflex agent program in Python for the vacuum-cleaner world problem. This program defines the States, intial state, Actions,sucessor function,goal test and Path Cost. For each possible initial state, the program returns a sequence of actions that leads to the goal state, along with the path cost. Generates two tes...
1.Enter LOCATION A/B in captial letters where A and B are the two adjacent rooms respectively.
2.Enter Status O/1 accordingly where 0 means CLEAN and 1 means DIRTY.
https://colab.research.google.com/drive/1oW6-BynOXgUT67FtnQQLXgcB-RUwyMr0?usp=sharing
Learn about the definition, properties, types and architectures of intelligent agents, with examples and diagrams. The slides cover topics such as sensors, effectors, rationality, autonomy, goals, utility and more.
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Example 3. Vacuum World. We have a vacuum cleaner and two rooms. Each room may or may not be dirty. The vacuum cleaner can move left or right (the action has no effect if there is no room to the right/left). The vacuum cleaner can suck; this cleans the room (even if the room was already clean). Physical states
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Oct 19, 2021 · Consider the simple vacuum-cleaner agent that cleans a square if it is dirty and moves to the other square if not; this is the agent function tabulated as follows. Percept sequence Action. [A,Clean] Right. [A,Dirty] Suck. [B,Clean] Left.
Vacuum Cleaner World. AB. CISC4/681 Introduction to Artificial Intelligence 6. • Percepts: which square (A or B); dirt? • Actions: move right, move left, suck, do nothing • Agent function: maps percept sequence into actions • Agent program: function’s implementation • How should the program act? 2 Rational Agent – does the right thing.
(University of Freiburg) Foundations of AI April 27, 2012 10 / 47 The Vacuum Cleaner Problem If the environment is completely observable, the vacuum cleaner always knows where it is and where the dirt is. The solution then is reduced to searching for a path from the initial state to the goal state. R L S S S R L R L R L S S S S L L L L R R R R
