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Added sections on learning.ipynb (aimacode#851)
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‎README.md

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@@ -109,8 +109,8 @@ Here is a table of algorithms, the figure, name of the algorithm in the book and
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| 9.6 | FOL-BC-Ask | `fol_bc_ask` | [`logic.py`][logic] | Done | |
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| 9.8 | Append | | | | |
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| 10.1 | Air-Cargo-problem | `air_cargo` | [`planning.py`][planning] | Done | Included |
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| 10.2 | Spare-Tire-Problem | `spare_tire` | [`planning.py`][planning] | Done | |
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| 10.3 | Three-Block-Tower | `three_block_tower` | [`planning.py`][planning] | Done | |
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| 10.2 | Spare-Tire-Problem | `spare_tire` | [`planning.py`][planning] | Done | Included |
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| 10.3 | Three-Block-Tower | `three_block_tower` | [`planning.py`][planning] | Done | Included |
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| 10.7 | Cake-Problem | `have_cake_and_eat_cake_too` | [`planning.py`][planning] | Done | |
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| 10.9 | Graphplan | `GraphPlan` | [`planning.py`][planning] | | |
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| 10.13 | Partial-Order-Planner | | | | |

‎planning.ipynb

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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"outputs": [],
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},
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"cell_type": "code",
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"metadata": {},
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{
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},
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"cell_type": "code",
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},
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{
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"cell_type": "code",
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"metadata": {},
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{
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"True"
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]
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},
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"execution_count": 18,
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"execution_count": 14,
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"metadata": {},
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"output_type": "execute_result"
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}
@@ -390,13 +390,209 @@
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"airCargo.goal_test()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"It has now achieved its goal."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## The Spare Tire Problem"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Let's consider the problem of changing a flat tire. The goal is to have a good spare tire properly mounted onto the car's axle, where the initial state has a flat tire on the axle and a good spare tire in the trunk. Let us now define an object of `spare_tire` problem:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 15,
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"metadata": {},
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"outputs": [],
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"source": [
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"It has now achieved its goal."
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"spare_tire = spare_tire()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Now, before taking any actions, we will check `spare_tire` if it has completed the goal it is required to do"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"False\n"
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]
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}
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],
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"source": [
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"print(spare_tire.goal_test())"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"As we can see, it hasn't completed the goal. Now, we define the sequence of actions that it should take in order to have a good spare tire properly mounted onto the car's axle. Then the `spare_tire` acts on each of them."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"metadata": {},
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"outputs": [],
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"source": [
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"solution = [expr(\"Remove(Flat, Axle)\"),\n",
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" expr(\"Remove(Spare, Trunk)\"),\n",
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" expr(\"PutOn(Spare, Axle)\")]\n",
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"\n",
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"for action in solution:\n",
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" spare_tire.act(action)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"As the `spare_tire` has taken all the steps it needed in order to achieve the goal, we can now check if it has acheived its goal"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"True\n"
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]
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}
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],
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"source": [
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"print(spare_tire.goal_test())"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"It has now successfully achieved its goal i.e, to have a good spare tire properly mounted onto the car's axle."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Three Block Tower Problem"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"This problem's domain consists of a set of cube-shaped blocks sitting on a table. The blocks can be stacked , but only one block can fit directly on top of another. A robot arm can pick up a block and move it to another position, either on the table or on top of another block. The arm can pick up only one block at a time, so it cannot pick up a block that has another one on it. The goal will always be to build one or more stacks of blocks. In our case, we consider only three blocks. Let us now define an object of `three_block_tower` problem:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"metadata": {},
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"outputs": [],
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"source": [
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"three_block_tower = three_block_tower()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Now, before taking any actions, we will check `three_tower_block` if it has completed the goal it is required to do"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"False\n"
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]
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}
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],
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"source": [
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"print(three_block_tower.goal_test())"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"As we can see, it hasn't completed the goal. Now, we define the sequence of actions that it should take in order to build a stack of three blocks. Then the `three_block_tower` acts on each of them."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 22,
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"metadata": {},
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"outputs": [],
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"source": [
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"solution = [expr(\"MoveToTable(C, A)\"),\n",
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" expr(\"Move(B, Table, C)\"),\n",
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" expr(\"Move(A, Table, B)\")]\n",
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"\n",
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"for action in solution:\n",
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" three_block_tower.act(action)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"As the `three_block_tower` has taken all the steps it needed in order to achieve the goal, we can now check if it has acheived its goal"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 24,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"True\n"
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]
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}
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],
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"source": [
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"print(three_block_tower.goal_test())"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"It has now successfully achieved its goal i.e, to build a stack of three blocks."
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]
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}
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],

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